Added "epoch" evaluation_strategy (#388)

src/axolotl/utils/trainer.py

@@ -451,6 +451,15 @@ def setup_trainer(cfg, train_dataset, eval_dataset, model, tokenizer, total_num_
             "sample_packing_efficiency"
         ] = 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
         # max_steps=total_num_steps,  # this is helpful in case we don't actually know total # of steps
         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,
         num_train_epochs=cfg.num_epochs,
         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",
         eval_steps=cfg.eval_steps if cfg.val_set_size > 0 else None,
         save_steps=cfg.save_steps,