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@@ -67,14 +67,15 @@ pre > code.sourceCode > span > a:first-child::before { text-decoration: underlin
<link href="../../favicon.jpg" rel="icon" type="image/jpeg">
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@@ -124,7 +125,8 @@ gtag('config', 'G-9KYCVJBNMQ', { 'anonymize_ip': true});
<div class="navbar-container container-fluid">
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<a href="../../index.html" class="navbar-brand navbar-brand-logo">
<img src="../../image/axolotl_logo_digital_white.svg" alt="" class="navbar-logo">
<img src="../../image/axolotl_logo_digital_white.svg" alt="" class="navbar-logo light-content">
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@@ -150,6 +152,10 @@ gtag('config', 'G-9KYCVJBNMQ', { 'anonymize_ip': true});
<div id="quarto-content" class="quarto-container page-columns page-rows-contents page-layout-article page-navbar">
<!-- sidebar -->
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<a href="../../index.html" class="sidebar-logo-link">
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@@ -551,37 +557,37 @@ gtag('config', 'G-9KYCVJBNMQ', { 'anonymize_ip': true});
</table>
<section id="axolotl.utils.schedulers.InterpolatingLogScheduler" class="level3">
<h3 class="anchored" data-anchor-id="axolotl.utils.schedulers.InterpolatingLogScheduler">InterpolatingLogScheduler</h3>
<div class="sourceCode" id="cb1"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a>utils.schedulers.InterpolatingLogScheduler(</span>
<div class="code-copy-outer-scaffold"><div class="sourceCode" id="cb1"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a>utils.schedulers.InterpolatingLogScheduler(</span>
<span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a> optimizer,</span>
<span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a> num_steps,</span>
<span id="cb1-4"><a href="#cb1-4" aria-hidden="true" tabindex="-1"></a> min_lr,</span>
<span id="cb1-5"><a href="#cb1-5" aria-hidden="true" tabindex="-1"></a> max_lr,</span>
<span id="cb1-6"><a href="#cb1-6" aria-hidden="true" tabindex="-1"></a> last_epoch<span class="op">=-</span><span class="dv">1</span>,</span>
<span id="cb1-7"><a href="#cb1-7" aria-hidden="true" tabindex="-1"></a>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<span id="cb1-7"><a href="#cb1-7" aria-hidden="true" tabindex="-1"></a>)</span></code></pre></div><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></div>
<p>A scheduler that interpolates learning rates in a logarithmic fashion</p>
</section>
<section id="axolotl.utils.schedulers.JaggedLRRestartScheduler" class="level3">
<h3 class="anchored" data-anchor-id="axolotl.utils.schedulers.JaggedLRRestartScheduler">JaggedLRRestartScheduler</h3>
<div class="sourceCode" id="cb2"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a>utils.schedulers.JaggedLRRestartScheduler(</span>
<div class="code-copy-outer-scaffold"><div class="sourceCode" id="cb2"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a>utils.schedulers.JaggedLRRestartScheduler(</span>
<span id="cb2-2"><a href="#cb2-2" aria-hidden="true" tabindex="-1"></a> optimizer,</span>
<span id="cb2-3"><a href="#cb2-3" aria-hidden="true" tabindex="-1"></a> inner_schedule,</span>
<span id="cb2-4"><a href="#cb2-4" aria-hidden="true" tabindex="-1"></a> jagged_restart_steps,</span>
<span id="cb2-5"><a href="#cb2-5" aria-hidden="true" tabindex="-1"></a> jagged_restart_warmup_steps,</span>
<span id="cb2-6"><a href="#cb2-6" aria-hidden="true" tabindex="-1"></a> jagged_restart_anneal_steps<span class="op">=</span><span class="dv">1</span>,</span>
<span id="cb2-7"><a href="#cb2-7" aria-hidden="true" tabindex="-1"></a> min_lr_scale<span class="op">=</span><span class="fl">0.001</span>,</span>
<span id="cb2-8"><a href="#cb2-8" aria-hidden="true" tabindex="-1"></a>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<span id="cb2-8"><a href="#cb2-8" aria-hidden="true" tabindex="-1"></a>)</span></code></pre></div><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></div>
<p>Wraps another scheduler to apply per-lora-restart learning rate warmups.</p>
</section>
<section id="axolotl.utils.schedulers.RexLR" class="level3">
<h3 class="anchored" data-anchor-id="axolotl.utils.schedulers.RexLR">RexLR</h3>
<div class="sourceCode" id="cb3"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a>utils.schedulers.RexLR(</span>
<div class="code-copy-outer-scaffold"><div class="sourceCode" id="cb3"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a>utils.schedulers.RexLR(</span>
<span id="cb3-2"><a href="#cb3-2" aria-hidden="true" tabindex="-1"></a> optimizer,</span>
<span id="cb3-3"><a href="#cb3-3" aria-hidden="true" tabindex="-1"></a> max_lr,</span>
<span id="cb3-4"><a href="#cb3-4" aria-hidden="true" tabindex="-1"></a> min_lr,</span>
<span id="cb3-5"><a href="#cb3-5" aria-hidden="true" tabindex="-1"></a> total_steps<span class="op">=</span><span class="dv">0</span>,</span>
<span id="cb3-6"><a href="#cb3-6" aria-hidden="true" tabindex="-1"></a> num_warmup_steps<span class="op">=</span><span class="dv">0</span>,</span>
<span id="cb3-7"><a href="#cb3-7" aria-hidden="true" tabindex="-1"></a> last_step<span class="op">=</span><span class="dv">0</span>,</span>
<span id="cb3-8"><a href="#cb3-8" aria-hidden="true" tabindex="-1"></a>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<span id="cb3-8"><a href="#cb3-8" aria-hidden="true" tabindex="-1"></a>)</span></code></pre></div><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></div>
<p>Reflected Exponential (REX) learning rate scheduler.</p>
<ul>
<li>Original implementation: https://github.com/IvanVassi/REX_LR</li>
@@ -673,12 +679,12 @@ gtag('config', 'G-9KYCVJBNMQ', { 'anonymize_ip': true});
</table>
<section id="axolotl.utils.schedulers.get_cosine_schedule_with_min_lr" class="level3">
<h3 class="anchored" data-anchor-id="axolotl.utils.schedulers.get_cosine_schedule_with_min_lr">get_cosine_schedule_with_min_lr</h3>
<div class="sourceCode" id="cb4"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb4-1"><a href="#cb4-1" aria-hidden="true" tabindex="-1"></a>utils.schedulers.get_cosine_schedule_with_min_lr(</span>
<div class="code-copy-outer-scaffold"><div class="sourceCode" id="cb4"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb4-1"><a href="#cb4-1" aria-hidden="true" tabindex="-1"></a>utils.schedulers.get_cosine_schedule_with_min_lr(</span>
<span id="cb4-2"><a href="#cb4-2" aria-hidden="true" tabindex="-1"></a> optimizer,</span>
<span id="cb4-3"><a href="#cb4-3" aria-hidden="true" tabindex="-1"></a> num_warmup_steps,</span>
<span id="cb4-4"><a href="#cb4-4" aria-hidden="true" tabindex="-1"></a> num_training_steps,</span>
<span id="cb4-5"><a href="#cb4-5" aria-hidden="true" tabindex="-1"></a> min_lr_ratio<span class="op">=</span><span class="fl">0.0</span>,</span>
<span id="cb4-6"><a href="#cb4-6" aria-hidden="true" tabindex="-1"></a>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<span id="cb4-6"><a href="#cb4-6" aria-hidden="true" tabindex="-1"></a>)</span></code></pre></div><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></div>
<section id="create-a-learning-rate-schedule-which-has" class="level4 doc-section doc-section-create-a-learning-rate-schedule-which-has">
<h4 class="doc-section doc-section-create-a-learning-rate-schedule-which-has anchored" data-anchor-id="create-a-learning-rate-schedule-which-has">Create a learning rate schedule which has</h4>
<ul>
@@ -689,13 +695,13 @@ gtag('config', 'G-9KYCVJBNMQ', { 'anonymize_ip': true});
</section>
<section id="axolotl.utils.schedulers.get_cosine_schedule_with_quadratic_warmup" class="level3">
<h3 class="anchored" data-anchor-id="axolotl.utils.schedulers.get_cosine_schedule_with_quadratic_warmup">get_cosine_schedule_with_quadratic_warmup</h3>
<div class="sourceCode" id="cb5"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb5-1"><a href="#cb5-1" aria-hidden="true" tabindex="-1"></a>utils.schedulers.get_cosine_schedule_with_quadratic_warmup(</span>
<div class="code-copy-outer-scaffold"><div class="sourceCode" id="cb5"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb5-1"><a href="#cb5-1" aria-hidden="true" tabindex="-1"></a>utils.schedulers.get_cosine_schedule_with_quadratic_warmup(</span>
<span id="cb5-2"><a href="#cb5-2" aria-hidden="true" tabindex="-1"></a> optimizer,</span>
<span id="cb5-3"><a href="#cb5-3" aria-hidden="true" tabindex="-1"></a> num_warmup_steps,</span>
<span id="cb5-4"><a href="#cb5-4" aria-hidden="true" tabindex="-1"></a> num_training_steps,</span>
<span id="cb5-5"><a href="#cb5-5" aria-hidden="true" tabindex="-1"></a> num_cycles<span class="op">=</span><span class="fl">0.5</span>,</span>
<span id="cb5-6"><a href="#cb5-6" aria-hidden="true" tabindex="-1"></a> last_epoch<span class="op">=-</span><span class="dv">1</span>,</span>
<span id="cb5-7"><a href="#cb5-7" aria-hidden="true" tabindex="-1"></a>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<span id="cb5-7"><a href="#cb5-7" aria-hidden="true" tabindex="-1"></a>)</span></code></pre></div><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></div>
<p>Create a schedule with a learning rate that decreases following the values of the cosine function between the
initial lr set in the optimizer to 0, after a warmup period during which it increases linearly between 0 and the
initial lr set in the optimizer.</p>
@@ -757,7 +763,7 @@ initial lr set in the optimizer.</p>
</section>
<section id="axolotl.utils.schedulers.get_cosine_schedule_with_warmup_decay_constant" class="level3">
<h3 class="anchored" data-anchor-id="axolotl.utils.schedulers.get_cosine_schedule_with_warmup_decay_constant">get_cosine_schedule_with_warmup_decay_constant</h3>
<div class="sourceCode" id="cb6"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb6-1"><a href="#cb6-1" aria-hidden="true" tabindex="-1"></a>utils.schedulers.get_cosine_schedule_with_warmup_decay_constant(</span>
<div class="code-copy-outer-scaffold"><div class="sourceCode" id="cb6"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb6-1"><a href="#cb6-1" aria-hidden="true" tabindex="-1"></a>utils.schedulers.get_cosine_schedule_with_warmup_decay_constant(</span>
<span id="cb6-2"><a href="#cb6-2" aria-hidden="true" tabindex="-1"></a> optimizer,</span>
<span id="cb6-3"><a href="#cb6-3" aria-hidden="true" tabindex="-1"></a> num_warmup_steps,</span>
<span id="cb6-4"><a href="#cb6-4" aria-hidden="true" tabindex="-1"></a> num_training_steps,</span>
@@ -765,7 +771,7 @@ initial lr set in the optimizer.</p>
<span id="cb6-6"><a href="#cb6-6" aria-hidden="true" tabindex="-1"></a> min_lr_ratio,</span>
<span id="cb6-7"><a href="#cb6-7" aria-hidden="true" tabindex="-1"></a> num_cycles<span class="op">=</span><span class="fl">0.5</span>,</span>
<span id="cb6-8"><a href="#cb6-8" aria-hidden="true" tabindex="-1"></a> last_epoch<span class="op">=-</span><span class="dv">1</span>,</span>
<span id="cb6-9"><a href="#cb6-9" aria-hidden="true" tabindex="-1"></a>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<span id="cb6-9"><a href="#cb6-9" aria-hidden="true" tabindex="-1"></a>)</span></code></pre></div><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></div>
<p>Implementation of Continual Pre-Training of Large Language Models: How to (re)warm your model? (https://arxiv.org/pdf/2308.04014.pdf)
Create a schedule with a learning rate that decreases following the values of the cosine function between the
initial lr set in the optimizer to min_lr_ratio until num_training_steps * constant_lr_ratio, after constant_rate returns constant value of min_rate
@@ -883,13 +889,14 @@ initial lr set in the optimizer to min_lr_ratio until num_training_steps * const
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