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actually print eval response

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Carl Philipp Klemm 2024-05-07 15:27:59 +02:00
parent 2ee4f294af
commit 65482b55a6
1 changed files with 1 additions and 1 deletions
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train_dynamic.py
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@ -78,7 +78,7 @@ def evaluate(model: DyntrainModel, tokenizer,
attention_mask = torch.ones(input_ids.shape, device=model.devices[0], requires_grad=False) attention_mask = torch.ones(input_ids.shape, device=model.devices[0], requires_grad=False)
outputs = model.generate(input_ids, attention_mask=attention_mask, do_sample=True, temperature=1, max_new_tokens=100) outputs = model.generate(input_ids, attention_mask=attention_mask, do_sample=True, temperature=1, max_new_tokens=100)
response_decoded = tokenizer.batch_decode(outputs, skip_special_tokens=True)[0] response_decoded = tokenizer.batch_decode(outputs, skip_special_tokens=True)[0]
print(f"Eval generation: response_decoded") print(f"Eval generation: {response_decoded}")
log_writer.add_text("Text/Eval", response_decoded, globalstep) log_writer.add_text("Text/Eval", response_decoded, globalstep)