End of training

README.md

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+---
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: tun_wav2vec8
+  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/myriam-charfeddine5/huggingface/runs/w8fp109b)
+[<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/myriam-charfeddine5/huggingface/runs/w8fp109b)
+# tun_wav2vec8
+
+This model was trained from scratch on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.2858
+- Wer: 0.5831
+- Cer: 0.1539
+
+## 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: 10
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 80
+- num_epochs: 100
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
+| 2.2416        | 5.0   | 300  | 1.6570          | 0.9561 | 0.3341 |
+| 0.6397        | 10.0  | 600  | 1.0742          | 0.8652 | 0.3005 |
+| 0.4434        | 15.0  | 900  | 1.2856          | 0.7743 | 0.2411 |
+| 0.3084        | 20.0  | 1200 | 1.0868          | 0.7335 | 0.2106 |
+| 0.2708        | 25.0  | 1500 | 0.9412          | 0.7367 | 0.1960 |
+| 0.2519        | 30.0  | 1800 | 0.8857          | 0.6959 | 0.1863 |
+| 0.1833        | 35.0  | 2100 | 1.2220          | 0.6740 | 0.1856 |
+| 0.1354        | 40.0  | 2400 | 1.1682          | 0.6520 | 0.1786 |
+| 0.1363        | 45.0  | 2700 | 1.1745          | 0.6865 | 0.1794 |
+| 0.129         | 50.0  | 3000 | 1.0153          | 0.6426 | 0.1736 |
+| 0.1036        | 55.0  | 3300 | 1.1114          | 0.6332 | 0.1705 |
+| 0.1011        | 60.0  | 3600 | 1.4662          | 0.6238 | 0.1794 |
+| 0.0902        | 65.0  | 3900 | 1.3797          | 0.6426 | 0.1779 |
+| 0.074         | 70.0  | 4200 | 1.4517          | 0.6207 | 0.1813 |
+| 0.0648        | 75.0  | 4500 | 1.2976          | 0.6207 | 0.1694 |
+| 0.0591        | 80.0  | 4800 | 1.3030          | 0.5987 | 0.1690 |
+| 0.0622        | 85.0  | 5100 | 1.2847          | 0.5925 | 0.1636 |
+| 0.0639        | 90.0  | 5400 | 1.3230          | 0.5925 | 0.1659 |
+| 0.0816        | 95.0  | 5700 | 1.2766          | 0.5925 | 0.1582 |
+| 0.0444        | 100.0 | 6000 | 1.2858          | 0.5831 | 0.1539 |
+
+
+### Framework versions
+
+- Transformers 4.42.3
+- Pytorch 2.1.2
+- Datasets 2.20.0
+- Tokenizers 0.19.1