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jessica-ecosia
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finetuning-llms-project-2

Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Eval Results
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End of training

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Files changed (3) hide show
  1. README.md +9 -9
  2. pytorch_model.bin +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -23,10 +23,10 @@ model-index:
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  metrics:
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  - name: F1
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  type: f1
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- value: 0.8650918975766398
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  - name: Accuracy
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  type: accuracy
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- value: 0.874828060522696
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -36,9 +36,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the financial_phrasebank dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5291
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- - F1: 0.8651
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- - Accuracy: 0.8748
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|
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- | 0.6006 | 0.94 | 100 | 0.3973 | 0.8203 | 0.8418 |
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- | 0.2798 | 1.89 | 200 | 0.3888 | 0.8334 | 0.8508 |
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- | 0.1398 | 2.83 | 300 | 0.4821 | 0.8474 | 0.8480 |
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- | 0.0611 | 3.77 | 400 | 0.5291 | 0.8651 | 0.8748 |
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  ### Framework versions
 
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  metrics:
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  - name: F1
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  type: f1
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+ value: 0.8330949180475766
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  - name: Accuracy
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  type: accuracy
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+ value: 0.8493810178817056
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the financial_phrasebank dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5427
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+ - F1: 0.8331
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+ - Accuracy: 0.8494
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|
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+ | 0.6137 | 0.94 | 100 | 0.5180 | 0.7614 | 0.8061 |
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+ | 0.297 | 1.89 | 200 | 0.4018 | 0.8201 | 0.8425 |
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+ | 0.1648 | 2.83 | 300 | 0.4641 | 0.8327 | 0.8521 |
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+ | 0.0736 | 3.77 | 400 | 0.5427 | 0.8331 | 0.8494 |
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  ### Framework versions
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