update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: hubert-base-libri-demo-feature_extractor_not_frozen_v1_30epochs_weight_decay
+  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. -->
+
+# hubert-base-libri-demo-feature_extractor_not_frozen_v1_30epochs_weight_decay
+
+This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 3.8346
+- Wer: 1.0000
+
+## 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: 0.00015
+- train_batch_size: 64
+- 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: 3000
+- num_epochs: 30
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Wer    |
+|:-------------:|:-----:|:-----:|:---------------:|:------:|
+| 4.3231        | 1.12  | 500   | 3.4739          | 1.0000 |
+| 2.879         | 2.24  | 1000  | 3.5811          | 1.0000 |
+| 2.8709        | 3.36  | 1500  | 3.9899          | 1.0000 |
+| 2.871         | 4.48  | 2000  | 4.0805          | 1.0000 |
+| 2.8706        | 5.61  | 2500  | 3.8464          | 1.0000 |
+| 2.8672        | 6.73  | 3000  | 3.7938          | 1.0000 |
+| 2.8709        | 7.85  | 3500  | 3.8578          | 1.0000 |
+| 2.8708        | 8.97  | 4000  | 3.7691          | 1.0000 |
+| 2.8678        | 10.09 | 4500  | 3.8619          | 1.0000 |
+| 2.8662        | 11.21 | 5000  | 3.8804          | 1.0000 |
+| 2.8664        | 12.33 | 5500  | 3.8169          | 1.0000 |
+| 2.8662        | 13.45 | 6000  | 3.6758          | 1.0000 |
+| 2.8654        | 14.57 | 6500  | 3.7314          | 1.0000 |
+| 2.8658        | 15.7  | 7000  | 3.8113          | 1.0000 |
+| 2.8647        | 16.82 | 7500  | 3.8938          | 1.0000 |
+| 2.8653        | 17.94 | 8000  | 3.9268          | 1.0000 |
+| 2.8652        | 19.06 | 8500  | 3.9288          | 1.0000 |
+| 2.8649        | 20.18 | 9000  | 3.9164          | 1.0000 |
+| 2.8654        | 21.3  | 9500  | 3.8781          | 1.0000 |
+| 2.8652        | 22.42 | 10000 | 3.8628          | 1.0000 |
+| 2.8642        | 23.54 | 10500 | 3.8646          | 1.0000 |
+| 2.8655        | 24.66 | 11000 | 3.8467          | 1.0000 |
+| 2.8658        | 25.78 | 11500 | 3.8157          | 1.0000 |
+| 2.8647        | 26.91 | 12000 | 3.8274          | 1.0000 |
+| 2.8648        | 28.03 | 12500 | 3.8022          | 1.0000 |
+| 2.8644        | 29.15 | 13000 | 3.8346          | 1.0000 |
+
+
+### Framework versions
+
+- Transformers 4.30.0.dev0
+- Pytorch 2.0.1
+- Datasets 2.12.1.dev0
+- Tokenizers 0.13.3