Added "epoch" evaluation_strategy (#388)
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@@ -451,6 +451,15 @@ def setup_trainer(cfg, train_dataset, eval_dataset, model, tokenizer, total_num_
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"sample_packing_efficiency"
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] = cfg.sample_packing_eff_est
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if cfg.val_set_size == 0:
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evaluation_strategy = "no"
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elif cfg.eval_steps < 1:
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# eval every epoch
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evaluation_strategy = "epoch"
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else:
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# eval every eval_steps steps
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evaluation_strategy = "steps"
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training_args = AxolotlTrainingArguments( # pylint: disable=unexpected-keyword-arg
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# max_steps=total_num_steps, # this is helpful in case we don't actually know total # of steps
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max_seq_length=cfg.sequence_len,
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@@ -462,7 +471,7 @@ def setup_trainer(cfg, train_dataset, eval_dataset, model, tokenizer, total_num_
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eval_accumulation_steps=cfg.gradient_accumulation_steps,
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num_train_epochs=cfg.num_epochs,
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learning_rate=cfg.learning_rate,
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evaluation_strategy="steps" if cfg.val_set_size > 0 else "no",
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evaluation_strategy=evaluation_strategy,
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save_strategy="steps" if cfg.save_steps else "epoch",
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eval_steps=cfg.eval_steps if cfg.val_set_size > 0 else None,
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save_steps=cfg.save_steps,
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