End of training

README.md

@@ -1,199 +1,97 @@
 ---
 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-nmcpc-nomi
+  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-nmcpc-nomi
+
+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: 0.3286
+- Wer: 0.3266
+
+## 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: 200
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch    | Step | Validation Loss | Wer    |
+|:-------------:|:--------:|:----:|:---------------:|:------:|
+| 4.8042        | 6.0606   | 200  | 3.0647          | 0.9452 |
+| 2.8665        | 12.1212  | 400  | 2.2960          | 0.9838 |
+| 1.4496        | 18.1818  | 600  | 0.5882          | 0.6085 |
+| 0.4807        | 24.2424  | 800  | 0.4014          | 0.4828 |
+| 0.275         | 30.3030  | 1000 | 0.4216          | 0.3996 |
+| 0.1757        | 36.3636  | 1200 | 0.2956          | 0.3651 |
+| 0.1298        | 42.4242  | 1400 | 0.4517          | 0.3712 |
+| 0.1018        | 48.4848  | 1600 | 0.4099          | 0.3529 |
+| 0.08          | 54.5455  | 1800 | 0.3337          | 0.3651 |
+| 0.0729        | 60.6061  | 2000 | 0.3765          | 0.3671 |
+| 0.0604        | 66.6667  | 2200 | 0.3915          | 0.3671 |
+| 0.0504        | 72.7273  | 2400 | 0.3723          | 0.3590 |
+| 0.0449        | 78.7879  | 2600 | 0.3246          | 0.3489 |
+| 0.0392        | 84.8485  | 2800 | 0.3044          | 0.3428 |
+| 0.036         | 90.9091  | 3000 | 0.2869          | 0.3286 |
+| 0.0424        | 96.9697  | 3200 | 0.3328          | 0.3408 |
+| 0.0308        | 103.0303 | 3400 | 0.3950          | 0.3387 |
+| 0.0296        | 109.0909 | 3600 | 0.3217          | 0.3306 |
+| 0.0209        | 115.1515 | 3800 | 0.3163          | 0.3347 |
+| 0.0179        | 121.2121 | 4000 | 0.3692          | 0.3387 |
+| 0.0234        | 127.2727 | 4200 | 0.3597          | 0.3327 |
+| 0.0141        | 133.3333 | 4400 | 0.3497          | 0.3266 |
+| 0.0125        | 139.3939 | 4600 | 0.3291          | 0.3225 |
+| 0.0125        | 145.4545 | 4800 | 0.3130          | 0.3185 |
+| 0.0116        | 151.5152 | 5000 | 0.3337          | 0.3327 |
+| 0.0117        | 157.5758 | 5200 | 0.3424          | 0.3367 |
+| 0.0088        | 163.6364 | 5400 | 0.3385          | 0.3347 |
+| 0.0087        | 169.6970 | 5600 | 0.3302          | 0.3266 |
+| 0.0062        | 175.7576 | 5800 | 0.3093          | 0.3286 |
+| 0.0064        | 181.8182 | 6000 | 0.3367          | 0.3286 |
+| 0.0053        | 187.8788 | 6200 | 0.3370          | 0.3306 |
+| 0.007         | 193.9394 | 6400 | 0.3354          | 0.3266 |
+| 0.0058        | 200.0    | 6600 | 0.3286          | 0.3266 |
+
+
+### Framework versions
+
+- Transformers 4.47.0.dev0
+- Pytorch 2.4.0
+- Datasets 3.0.1
+- Tokenizers 0.20.0

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