Model save

README.md

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+---
+tags:
+- generated_from_trainer
+datasets:
+- timit_asr
+metrics:
+- wer
+model-index:
+- name: wav2vec2-base-gumbelVQ-timit-fine-tuned
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: timit_asr
+      type: timit_asr
+      config: clean
+      split: test
+      args: clean
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.4901798635517883
+---
+
+<!-- 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. -->
+
+# wav2vec2-base-gumbelVQ-timit-fine-tuned
+
+This model was trained from scratch on the timit_asr dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7549
+- Wer: 0.4902
+
+## 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: 32
+- eval_batch_size: 1
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 1000
+- num_epochs: 20.0
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 0.4628        | 10.0  | 1450 | 0.6779          | 0.5171 |
+| 0.3036        | 20.0  | 2900 | 0.7549          | 0.4902 |
+
+
+### Framework versions
+
+- Transformers 4.36.2
+- Pytorch 2.3.0.dev20231229+cu118
+- Datasets 2.16.0
+- Tokenizers 0.15.0