Yassmen commited on
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End of training

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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/jkpfolor)
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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: 0.4582
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- - Accuracy: 0.8324
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- - F1: 0.8237
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- - Recall: 0.8324
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- - Precision: 0.8350
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  ## Model description
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@@ -51,15 +51,15 @@ The following hyperparameters were used during training:
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
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- - training_steps: 366
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  - mixed_precision_training: Native AMP
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
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- | 0.9245 | 0.9973 | 183 | 0.6705 | 0.7448 | 0.7246 | 0.7448 | 0.7586 |
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- | 0.7313 | 1.9946 | 366 | 0.4582 | 0.8324 | 0.8237 | 0.8324 | 0.8350 |
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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/tpmsep4l)
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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: 1.0650
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+ - Accuracy: 0.6143
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+ - F1: 0.6031
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+ - Recall: 0.6143
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+ - Precision: 0.6096
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  ## Model description
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
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+ - training_steps: 1467
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  - mixed_precision_training: Native AMP
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision |
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  |:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
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+ | 1.1536 | 0.9990 | 733 | 1.3164 | 0.5261 | 0.5101 | 0.5261 | 0.5250 |
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+ | 0.805 | 1.9993 | 1467 | 1.0650 | 0.6143 | 0.6031 | 0.6143 | 0.6096 |
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  ### Framework versions
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