susmitabhatt
/

xlsr-nm-nomo

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 ---
 library_name: transformers
-tags: []
 ---
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 ---
 library_name: transformers
+license: apache-2.0
+base_model: facebook/wav2vec2-large-xlsr-53
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: xlsr-nm-nomo
+  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. -->
+# xlsr-nm-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: 1.0423
+- Wer: 0.3916
+## 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    |
+|:-------------:|:-------:|:----:|:---------------:|:------:|
+| 4.7334        | 6.4590  | 200  | 3.1082          | 1.0    |
+| 2.9544        | 12.9180 | 400  | 2.8429          | 0.9956 |
+| 2.0771        | 19.3607 | 600  | 1.2204          | 0.8341 |
+| 0.7271        | 25.8197 | 800  | 1.0868          | 0.5531 |
+| 0.3103        | 32.2623 | 1000 | 1.0536          | 0.4912 |
+| 0.1852        | 38.7213 | 1200 | 0.9030          | 0.4469 |
+| 0.1399        | 45.1639 | 1400 | 0.8980          | 0.4491 |
+| 0.0864        | 51.6230 | 1600 | 0.8315          | 0.4292 |
+| 0.0643        | 58.0656 | 1800 | 0.9488          | 0.4004 |
+| 0.0525        | 64.5246 | 2000 | 0.9354          | 0.4137 |
+| 0.0455        | 70.9836 | 2200 | 0.9717          | 0.4093 |
+| 0.0383        | 77.4262 | 2400 | 0.9781          | 0.4004 |
+| 0.0261        | 83.8852 | 2600 | 1.1244          | 0.3938 |
+| 0.0265        | 90.3279 | 2800 | 1.0439          | 0.4004 |
+| 0.0197        | 96.7869 | 3000 | 1.0423          | 0.3916 |
+### Framework versions
+- Transformers 4.47.0.dev0
+- Pytorch 2.4.0
+- Datasets 3.0.1
+- Tokenizers 0.20.0

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