Model save

README.md

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+---
+license: apache-2.0
+base_model: facebook/wav2vec2-large-xlsr-53
+tags:
+- generated_from_trainer
+metrics:
+- wer
+- accuracy
+model-index:
+- name: asr-nepali
+  results: []
+---
+
+<!-- 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. -->
+
+# asr-nepali
+
+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: nan
+- Wer: 1.0
+- Cer: 0.9965
+- Accuracy: 0.0035
+
+## 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: 180
+- num_epochs: 30
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer | Cer    | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---:|:------:|:--------:|
+| 451.545       | 1.46  | 100  | 43.3285         | 1.0 | 0.9684 | 0.0316   |
+| 194.4567      | 2.92  | 200  | nan             | 1.0 | 0.9965 | 0.0035   |
+| 0.0           | 4.38  | 300  | nan             | 1.0 | 0.9965 | 0.0035   |
+| 0.0           | 5.84  | 400  | nan             | 1.0 | 0.9965 | 0.0035   |
+| 0.0           | 7.3   | 500  | nan             | 1.0 | 0.9965 | 0.0035   |
+| 0.0           | 8.76  | 600  | nan             | 1.0 | 0.9965 | 0.0035   |
+| 0.0           | 10.22 | 700  | nan             | 1.0 | 0.9965 | 0.0035   |
+| 0.0           | 11.68 | 800  | nan             | 1.0 | 0.9965 | 0.0035   |
+| 0.0           | 13.14 | 900  | nan             | 1.0 | 0.9965 | 0.0035   |
+| 0.0           | 14.6  | 1000 | nan             | 1.0 | 0.9965 | 0.0035   |
+| 0.0           | 16.06 | 1100 | nan             | 1.0 | 0.9965 | 0.0035   |
+| 0.0           | 17.52 | 1200 | nan             | 1.0 | 0.9965 | 0.0035   |
+| 0.0           | 18.98 | 1300 | nan             | 1.0 | 0.9965 | 0.0035   |
+| 0.0           | 20.44 | 1400 | nan             | 1.0 | 0.9965 | 0.0035   |
+| 0.0           | 21.9  | 1500 | nan             | 1.0 | 0.9965 | 0.0035   |
+| 0.0           | 23.36 | 1600 | nan             | 1.0 | 0.9965 | 0.0035   |
+| 0.0           | 24.82 | 1700 | nan             | 1.0 | 0.9965 | 0.0035   |
+| 0.0           | 26.28 | 1800 | nan             | 1.0 | 0.9965 | 0.0035   |
+| 0.0           | 27.74 | 1900 | nan             | 1.0 | 0.9965 | 0.0035   |
+| 0.0           | 29.2  | 2000 | nan             | 1.0 | 0.9965 | 0.0035   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.0

model.safetensors

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