End of training

README.md

@@ -1,199 +1,93 @@
 ---
 library_name: transformers
-tags: []
+license: apache-2.0
+base_model: facebook/wav2vec2-large-xlsr-53
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: xlsr-nm-nomimose
+  results: []
 ---
 
-# Model Card for Model ID
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-<!-- Provide a quick summary of what the model is/does. -->
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-## Model Details
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-### Model Description
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-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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+<!-- 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. -->
+
+# xlsr-nm-nomimose
+
+This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9684
+- Wer: 0.4369
+
+## 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: 0.0004
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 132
+- num_epochs: 100
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | Wer    |
+|:-------------:|:-------:|:----:|:---------------:|:------:|
+| 4.9556        | 3.3932  | 200  | 3.0924          | 1.0    |
+| 3.024         | 6.7863  | 400  | 2.8991          | 0.9943 |
+| 2.7554        | 10.1709 | 600  | 2.4531          | 1.0    |
+| 2.1877        | 13.5641 | 800  | 1.6865          | 0.9181 |
+| 1.247         | 16.9573 | 1000 | 1.1531          | 0.7247 |
+| 0.7161        | 20.3419 | 1200 | 1.0237          | 0.6052 |
+| 0.4613        | 23.7350 | 1400 | 0.9152          | 0.5631 |
+| 0.3173        | 27.1197 | 1600 | 0.8917          | 0.5165 |
+| 0.2399        | 30.5128 | 1800 | 0.8512          | 0.5256 |
+| 0.1871        | 33.9060 | 2000 | 0.9078          | 0.4937 |
+| 0.1536        | 37.2906 | 2200 | 0.9574          | 0.4972 |
+| 0.1259        | 40.6838 | 2400 | 0.9938          | 0.4903 |
+| 0.1095        | 44.0684 | 2600 | 1.0196          | 0.4994 |
+| 0.0947        | 47.4615 | 2800 | 0.9235          | 0.4778 |
+| 0.073         | 50.8547 | 3000 | 1.1352          | 0.4972 |
+| 0.068         | 54.2393 | 3200 | 0.9595          | 0.4778 |
+| 0.0562        | 57.6325 | 3400 | 1.0105          | 0.4710 |
+| 0.0564        | 61.0171 | 3600 | 1.0297          | 0.4744 |
+| 0.052         | 64.4103 | 3800 | 1.0371          | 0.4562 |
+| 0.0371        | 67.8034 | 4000 | 1.0999          | 0.4733 |
+| 0.034         | 71.1880 | 4200 | 1.0486          | 0.4699 |
+| 0.039         | 74.5812 | 4400 | 0.9800          | 0.4585 |
+| 0.031         | 77.9744 | 4600 | 0.9614          | 0.4494 |
+| 0.0323        | 81.3590 | 4800 | 0.9838          | 0.4551 |
+| 0.0229        | 84.7521 | 5000 | 1.0129          | 0.4334 |
+| 0.0232        | 88.1368 | 5200 | 0.9266          | 0.4243 |
+| 0.0144        | 91.5299 | 5400 | 0.9751          | 0.4334 |
+| 0.0178        | 94.9231 | 5600 | 0.9619          | 0.4369 |
+| 0.0147        | 98.3077 | 5800 | 0.9684          | 0.4369 |
+
+
+### Framework versions
+
+- Transformers 4.47.0.dev0
+- Pytorch 2.4.0
+- Datasets 3.0.1
+- Tokenizers 0.20.0

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