Repeating eval-F1 scores with seed + data randomization

[John6666]

I wonder if the model output has reached the ideal value…

Same metrics after every epoch

This is a duplicate of a question I’ve posted on Stack Overflow that until now has gotten no answers (link to SO post). Basically, I’m using the Trainer class to fine tune a model on a text classification task and the metrics I’m tracking are taking on the same values after every epoch - changing LR and batch size does not seem to change anything. This is the code I’m currently using: def compute_metrics(eval_preds): logits, labels = eval_preds preds = np.argmax(logits, axis=-1) …

F1 - a Hugging Face Space by evaluate-metric