Model save

README.md

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+---
+license: apache-2.0
+base_model: facebook/wav2vec2-large-xlsr-53
+tags:
+- generated_from_trainer
+datasets:
+- common_voice_6_1
+metrics:
+- wer
+model-index:
+- name: wav2vec2-common_voice-ta
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: common_voice_6_1
+      type: common_voice_6_1
+      config: ta
+      split: test
+      args: ta
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.7094281298299846
+---
+
+<!-- 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-common_voice-ta
+
+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_6_1 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6599
+- Wer: 0.7094
+
+## 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: 15.0
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| No log        | 0.84  | 100  | 4.3941          | 1.0    |
+| No log        | 1.69  | 200  | 3.2005          | 1.0    |
+| No log        | 2.53  | 300  | 2.7844          | 1.0145 |
+| No log        | 3.38  | 400  | 0.8691          | 1.0003 |
+| 4.317         | 4.22  | 500  | 0.6846          | 0.8394 |
+| 4.317         | 5.06  | 600  | 0.6270          | 0.7790 |
+| 4.317         | 5.91  | 700  | 0.5935          | 0.7802 |
+| 4.317         | 6.75  | 800  | 0.5701          | 0.7812 |
+| 4.317         | 7.59  | 900  | 0.5649          | 0.7891 |
+| 0.3656        | 8.44  | 1000 | 0.6092          | 0.8178 |
+| 0.3656        | 9.28  | 1100 | 0.6093          | 0.7721 |
+| 0.3656        | 10.13 | 1200 | 0.6154          | 0.7287 |
+| 0.3656        | 10.97 | 1300 | 0.6284          | 0.7408 |
+| 0.3656        | 11.81 | 1400 | 0.6343          | 0.7143 |
+| 0.1681        | 12.66 | 1500 | 0.6523          | 0.7363 |
+| 0.1681        | 13.5  | 1600 | 0.6543          | 0.7139 |
+| 0.1681        | 14.35 | 1700 | 0.6599          | 0.7094 |
+
+
+### Framework versions
+
+- Transformers 4.38.0.dev0
+- Pytorch 2.1.0+cu121
+- Datasets 2.17.0
+- Tokenizers 0.15.1

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runs/Feb09_15-12-11_96d880c2e067/events.out.tfevents.1707491669.96d880c2e067.6291.0

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