add support for include_tokens_per_second in training args (#2269)

* add support for include_tokens_per_second in training args

* Update docs/config.qmd

Co-authored-by: NanoCode012 <nano@axolotl.ai>

* Update src/axolotl/core/trainer_builder.py

Co-authored-by: NanoCode012 <nano@axolotl.ai>

---------

Co-authored-by: NanoCode012 <nano@axolotl.ai>

docs/config.qmd

@@ -390,6 +390,9 @@ save_total_limit: # Checkpoints saved at a time
 # e.g., when 1 epoch is 1000 steps => `num_epochs: 2` and `max_steps: 100` will train for 100 steps
 max_steps:
 
+# bool of whether to include tokens trainer per second in the training metrics. This iterates over the entire dataset once, so it takes some time.
+include_tokens_per_second:
+
 eval_table_size: # Approximate number of predictions sent to wandb depending on batch size. Enabled above 0. Default is 0
 eval_max_new_tokens: # Total number of tokens generated for predictions sent to wandb. Default is 128
 eval_causal_lm_metrics: # HF evaluate metrics used during evaluation. Default is ["sacrebleu", "comet", "ter", "chrf", "perplexity"]

src/axolotl/core/trainer_builder.py

@@ -330,6 +330,12 @@ class HFCausalTrainerBuilder(TrainerBuilderBase):
         )
 
         training_arguments_kwargs = {}
+
+        if self.cfg.include_tokens_per_second is not None:
+            training_arguments_kwargs[
+                "include_tokens_per_second"
+            ] = self.cfg.include_tokens_per_second
+
         if self.cfg.bf16 == "full":
             training_arguments_kwargs["bf16_full_eval"] = True
         else:

src/axolotl/utils/config/models/input/v0_4_1/__init__.py

@@ -844,6 +844,7 @@ class AxolotlInputConfig(
     save_only_model: Optional[bool] = False
     use_tensorboard: Optional[bool] = None
     profiler_steps: Optional[int] = None
+    include_tokens_per_second: Optional[bool] = None
 
     neftune_noise_alpha: Optional[float] = None