End of training

README.md

@@ -1,199 +1,106 @@
 ---
 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-a-nomo
+  results: []
 ---
 
-# Model Card for Model ID
-
-<!-- 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-a-nomo
+
+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: 0.6748
+- Wer: 0.3390
+
+## 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    |
+|:-------------:|:-------:|:----:|:---------------:|:------:|
+| 4.3851        | 2.3529  | 200  | 2.4270          | 1.0    |
+| 1.3933        | 4.7059  | 400  | 0.5187          | 0.6193 |
+| 0.2417        | 7.0588  | 600  | 0.4328          | 0.4403 |
+| 0.1174        | 9.4118  | 800  | 0.4113          | 0.4186 |
+| 0.08          | 11.7647 | 1000 | 0.3914          | 0.3589 |
+| 0.0509        | 14.1176 | 1200 | 0.4065          | 0.3665 |
+| 0.0445        | 16.4706 | 1400 | 0.4714          | 0.3636 |
+| 0.0329        | 18.8235 | 1600 | 0.3930          | 0.3561 |
+| 0.0315        | 21.1765 | 1800 | 0.5501          | 0.3655 |
+| 0.0298        | 23.5294 | 2000 | 0.4462          | 0.3561 |
+| 0.0366        | 25.8824 | 2200 | 0.4993          | 0.3447 |
+| 0.0259        | 28.2353 | 2400 | 0.5077          | 0.3561 |
+| 0.0197        | 30.5882 | 2600 | 0.5029          | 0.3466 |
+| 0.0229        | 32.9412 | 2800 | 0.4760          | 0.3400 |
+| 0.0174        | 35.2941 | 3000 | 0.5118          | 0.3475 |
+| 0.0102        | 37.6471 | 3200 | 0.5630          | 0.3428 |
+| 0.0104        | 40.0    | 3400 | 0.5598          | 0.3400 |
+| 0.015         | 42.3529 | 3600 | 0.5226          | 0.3428 |
+| 0.0102        | 44.7059 | 3800 | 0.5421          | 0.3513 |
+| 0.012         | 47.0588 | 4000 | 0.5936          | 0.3456 |
+| 0.0101        | 49.4118 | 4200 | 0.5772          | 0.3485 |
+| 0.009         | 51.7647 | 4400 | 0.5759          | 0.3438 |
+| 0.0104        | 54.1176 | 4600 | 0.5755          | 0.3400 |
+| 0.0118        | 56.4706 | 4800 | 0.5868          | 0.3362 |
+| 0.0118        | 58.8235 | 5000 | 0.6174          | 0.3456 |
+| 0.0109        | 61.1765 | 5200 | 0.6037          | 0.3390 |
+| 0.0086        | 63.5294 | 5400 | 0.5903          | 0.3447 |
+| 0.0039        | 65.8824 | 5600 | 0.5894          | 0.3428 |
+| 0.0058        | 68.2353 | 5800 | 0.6388          | 0.3428 |
+| 0.0044        | 70.5882 | 6000 | 0.6378          | 0.3390 |
+| 0.0032        | 72.9412 | 6200 | 0.6868          | 0.3409 |
+| 0.0057        | 75.2941 | 6400 | 0.6439          | 0.3419 |
+| 0.0034        | 77.6471 | 6600 | 0.6888          | 0.3381 |
+| 0.0022        | 80.0    | 6800 | 0.7217          | 0.3381 |
+| 0.0032        | 82.3529 | 7000 | 0.5946          | 0.3371 |
+| 0.0033        | 84.7059 | 7200 | 0.6650          | 0.3390 |
+| 0.0018        | 87.0588 | 7400 | 0.6844          | 0.3371 |
+| 0.0026        | 89.4118 | 7600 | 0.7199          | 0.3409 |
+| 0.0028        | 91.7647 | 7800 | 0.6868          | 0.3381 |
+| 0.002         | 94.1176 | 8000 | 0.6752          | 0.3409 |
+| 0.0013        | 96.4706 | 8200 | 0.6788          | 0.3390 |
+| 0.0011        | 98.8235 | 8400 | 0.6748          | 0.3390 |
+
+
+### Framework versions
+
+- Transformers 4.47.0.dev0
+- Pytorch 2.4.0
+- Datasets 3.0.1
+- Tokenizers 0.20.0

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