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mixed_model_finetuned_iemocap

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  1. README.md +8 -8
  2. model.safetensors +1 -1
  3. runs/Aug09_21-40-29_ed27fc0746bb/events.out.tfevents.1723239662.ed27fc0746bb.34.0 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -14,16 +14,16 @@ model-index:
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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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  should probably proofread and complete it, then remove this comment. -->
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- [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/yassmenyoussef55-arete-global/huggingface/runs/4ivdkvc9)
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  # mixed_model_finetuned_iemocap
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  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.9812
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- - Accuracy: 0.6334
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- - F1: 0.6228
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- - Recall: 0.6334
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- - Precision: 0.6215
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
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- | 1.2498 | 0.9990 | 733 | 1.3149 | 0.4961 | 0.4788 | 0.4961 | 0.5102 |
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- | 0.7868 | 1.9993 | 1467 | 0.9812 | 0.6334 | 0.6228 | 0.6334 | 0.6215 |
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  ### Framework versions
 
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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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  should probably proofread and complete it, then remove this comment. -->
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+ [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/yassmenyoussef55-arete-global/huggingface/runs/nt10409b)
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  # mixed_model_finetuned_iemocap
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  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.9738
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+ - Accuracy: 0.6344
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+ - F1: 0.6234
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+ - Recall: 0.6344
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+ - Precision: 0.6261
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
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+ | 1.1804 | 0.9990 | 733 | 1.1261 | 0.5639 | 0.5448 | 0.5639 | 0.5662 |
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+ | 0.7794 | 1.9993 | 1467 | 0.9738 | 0.6344 | 0.6234 | 0.6344 | 0.6261 |
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  ### Framework versions
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