End of training

README.md

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+---
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- recall
+- precision
+model-index:
+- name: mixed_model_finetuned_iemocap
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+[<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)
+# mixed_model_finetuned_iemocap
+
+This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9812
+- Accuracy: 0.6334
+- F1: 0.6228
+- Recall: 0.6334
+- Precision: 0.6215
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0001
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- training_steps: 1467
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     | Recall | Precision |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
+| 1.2498        | 0.9990 | 733  | 1.3149          | 0.4961   | 0.4788 | 0.4961 | 0.5102    |
+| 0.7868        | 1.9993 | 1467 | 0.9812          | 0.6334   | 0.6228 | 0.6334 | 0.6215    |
+
+
+### Framework versions
+
+- Transformers 4.42.3
+- Pytorch 2.1.2
+- Datasets 2.20.0
+- Tokenizers 0.19.1

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