End of training

README.md

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+---
+license: apache-2.0
+base_model: facebook/wav2vec2-large-xlsr-53
+tags:
+- generated_from_trainer
+datasets:
+- common_voice_13_0
+metrics:
+- wer
+model-index:
+- name: wav2vec2-large-xlsr-common_voice_13_0-id
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: common_voice_13_0
+      type: common_voice_13_0
+      config: id
+      split: test
+      args: id
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.4316463864306785
+---
+
+<!-- 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-large-xlsr-common_voice_13_0-id
+
+This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice_13_0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4115
+- Wer: 0.4316
+
+## 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: 0.0003
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 30
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 5.0656        | 2.88  | 400  | 2.7637          | 1.0    |
+| 1.1404        | 5.76  | 800  | 0.4483          | 0.6088 |
+| 0.3698        | 8.63  | 1200 | 0.4029          | 0.5278 |
+| 0.2695        | 11.51 | 1600 | 0.3976          | 0.5036 |
+| 0.2074        | 14.39 | 2000 | 0.3988          | 0.4793 |
+| 0.1796        | 17.27 | 2400 | 0.3952          | 0.4590 |
+| 0.1523        | 20.14 | 2800 | 0.3986          | 0.4463 |
+| 0.1352        | 23.02 | 3200 | 0.4143          | 0.4374 |
+| 0.121         | 25.9  | 3600 | 0.4022          | 0.4337 |
+| 0.1085        | 28.78 | 4000 | 0.4115          | 0.4316 |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu118
+- Datasets 2.15.0
+- Tokenizers 0.15.0

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