End of training

README.md

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+---
+license: cc-by-nc-4.0
+base_model: facebook/mms-1b-all
+tags:
+- generated_from_trainer
+datasets:
+- common_voice_15_0
+metrics:
+- wer
+model-index:
+- name: wav2vec2-large-mms-1b-azerbaijani-common_voice15.0
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: common_voice_15_0
+      type: common_voice_15_0
+      config: az
+      split: test
+      args: az
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.2631578947368421
+---
+
+<!-- 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-mms-1b-azerbaijani-common_voice15.0
+
+This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the common_voice_15_0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3188
+- Wer: 0.2632
+
+## 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: 0.001
+- train_batch_size: 16
+- 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: 100
+- num_epochs: 15
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 7.6471        | 2.0   | 10   | 7.6790          | 1.0658 |
+| 5.6745        | 4.0   | 20   | 4.2727          | 1.0088 |
+| 3.5016        | 6.0   | 30   | 3.1003          | 1.0    |
+| 2.6223        | 8.0   | 40   | 1.8137          | 1.0439 |
+| 1.3939        | 10.0  | 50   | 0.6549          | 0.3947 |
+| 0.3696        | 12.0  | 60   | 0.3665          | 0.2719 |
+| 0.2475        | 14.0  | 70   | 0.3188          | 0.2632 |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.1+cu121
+- Datasets 2.15.0
+- Tokenizers 0.15.0

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