End of training

README.md

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 ---
 library_name: transformers
-tags: []
+license: cc-by-nc-4.0
+base_model: facebook/mms-1b-all
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: Kabardian-ASR-colab3
+  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. -->
+
+# Kabardian-ASR-colab3
+
+This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1713
+- Wer: 0.3087
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Use OptimizerNames.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: 100
+- num_epochs: 6
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Wer    |
+|:-------------:|:------:|:----:|:---------------:|:------:|
+| 0.8505        | 0.1871 | 200  | 0.4842          | 0.8062 |
+| 0.6677        | 0.3742 | 400  | 0.4299          | 0.7603 |
+| 0.5938        | 0.5613 | 600  | 0.3595          | 0.6693 |
+| 0.5221        | 0.7484 | 800  | 0.3258          | 0.6032 |
+| 0.5563        | 0.9355 | 1000 | 0.3061          | 0.5789 |
+| 0.5082        | 1.1225 | 1200 | 0.2644          | 0.4787 |
+| 0.5271        | 1.3096 | 1400 | 0.2666          | 0.4908 |
+| 0.4715        | 1.4967 | 1600 | 0.2637          | 0.4558 |
+| 0.5146        | 1.6838 | 1800 | 0.2508          | 0.4528 |
+| 0.4727        | 1.8709 | 2000 | 0.2383          | 0.4220 |
+| 0.467         | 2.0580 | 2200 | 0.2298          | 0.4124 |
+| 0.449         | 2.2451 | 2400 | 0.2245          | 0.4014 |
+| 0.4389        | 2.4322 | 2600 | 0.2138          | 0.3778 |
+| 0.4332        | 2.6193 | 2800 | 0.2122          | 0.3919 |
+| 0.4239        | 2.8064 | 3000 | 0.2126          | 0.4074 |
+| 0.4228        | 2.9935 | 3200 | 0.2019          | 0.3658 |
+| 0.4119        | 3.1805 | 3400 | 0.2086          | 0.3789 |
+| 0.4034        | 3.3676 | 3600 | 0.1985          | 0.3632 |
+| 0.4098        | 3.5547 | 3800 | 0.2000          | 0.3536 |
+| 0.3788        | 3.7418 | 4000 | 0.1974          | 0.3686 |
+| 0.3758        | 3.9289 | 4200 | 0.2005          | 0.3947 |
+| 0.4135        | 4.1160 | 4400 | 0.1840          | 0.3492 |
+| 0.3503        | 4.3031 | 4600 | 0.1830          | 0.3373 |
+| 0.3556        | 4.4902 | 4800 | 0.1788          | 0.3253 |
+| 0.3227        | 4.6773 | 5000 | 0.1804          | 0.3234 |
+| 0.3259        | 4.8644 | 5200 | 0.1778          | 0.3228 |
+| 0.3577        | 5.0514 | 5400 | 0.1789          | 0.3248 |
+| 0.3307        | 5.2385 | 5600 | 0.1752          | 0.3161 |
+| 0.346         | 5.4256 | 5800 | 0.1756          | 0.3114 |
+| 0.329         | 5.6127 | 6000 | 0.1728          | 0.3162 |
+| 0.3188        | 5.7998 | 6200 | 0.1719          | 0.3167 |
+| 0.3149        | 5.9869 | 6400 | 0.1713          | 0.3087 |
+
+
+### Framework versions
+
+- Transformers 4.50.0.dev0
+- Pytorch 2.5.1+cu121
+- Datasets 3.3.2
+- Tokenizers 0.21.0

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