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Added "epoch" evaluation_strategy (#388)

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florian peyron
2023-08-14 16:59:23 +02:00
committed by GitHub
parent 73a0b6ead5
commit 5d48a10548
1 changed files with 10 additions and 1 deletions
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11
src/axolotl/utils/trainer.py
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@@ -451,6 +451,15 @@ def setup_trainer(cfg, train_dataset, eval_dataset, model, tokenizer, total_num_
"sample_packing_efficiency" "sample_packing_efficiency"
] = cfg.sample_packing_eff_est ] = cfg.sample_packing_eff_est
if cfg.val_set_size == 0:
evaluation_strategy = "no"
elif cfg.eval_steps < 1:
# eval every epoch
evaluation_strategy = "epoch"
else:
# eval every eval_steps steps
evaluation_strategy = "steps"
training_args = AxolotlTrainingArguments( # pylint: disable=unexpected-keyword-arg training_args = AxolotlTrainingArguments( # pylint: disable=unexpected-keyword-arg
# max_steps=total_num_steps, # this is helpful in case we don't actually know total # of steps # max_steps=total_num_steps, # this is helpful in case we don't actually know total # of steps
max_seq_length=cfg.sequence_len, max_seq_length=cfg.sequence_len,
@@ -462,7 +471,7 @@ def setup_trainer(cfg, train_dataset, eval_dataset, model, tokenizer, total_num_
eval_accumulation_steps=cfg.gradient_accumulation_steps, eval_accumulation_steps=cfg.gradient_accumulation_steps,
num_train_epochs=cfg.num_epochs, num_train_epochs=cfg.num_epochs,
learning_rate=cfg.learning_rate, learning_rate=cfg.learning_rate,
evaluation_strategy="steps" if cfg.val_set_size > 0 else "no", evaluation_strategy=evaluation_strategy,
save_strategy="steps" if cfg.save_steps else "epoch", save_strategy="steps" if cfg.save_steps else "epoch",
eval_steps=cfg.eval_steps if cfg.val_set_size > 0 else None, eval_steps=cfg.eval_steps if cfg.val_set_size > 0 else None,
save_steps=cfg.save_steps, save_steps=cfg.save_steps,