ihanif
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pashto-asr-v3

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 ---
+license: mit
+base_model: facebook/w2v-bert-2.0
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: pashto-asr-v3
+  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. -->
+# pashto-asr-v3
+This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1448
+- Wer: 0.1396
+## 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: 5e-05
+- train_batch_size: 4
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 8
+- 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: 500
+- training_steps: 1300
+- mixed_precision_training: Native AMP
+### Training results
+| Training Loss | Epoch   | Step | Validation Loss | Wer    |
+|:-------------:|:-------:|:----:|:---------------:|:------:|
+| 2.9698        | 0.8089  | 100  | 2.8928          | 0.9991 |
+| 0.8095        | 1.6178  | 200  | 0.6035          | 0.4036 |
+| 0.6152        | 2.4267  | 300  | 0.4857          | 0.3593 |
+| 0.3951        | 3.2356  | 400  | 0.4661          | 0.3505 |
+| 0.5493        | 4.0445  | 500  | 0.3651          | 0.2779 |
+| 0.4588        | 4.8534  | 600  | 0.3244          | 0.2632 |
+| 0.3616        | 5.6623  | 700  | 0.2954          | 0.2490 |
+| 0.1938        | 6.4712  | 800  | 0.2655          | 0.2341 |
+| 0.2047        | 7.2801  | 900  | 0.2510          | 0.2022 |
+| 0.2596        | 8.0890  | 1000 | 0.1953          | 0.1756 |
+| 0.1871        | 8.8979  | 1100 | 0.1716          | 0.1642 |
+| 0.0768        | 9.7068  | 1200 | 0.1559          | 0.1554 |
+| 0.1021        | 10.5157 | 1300 | 0.1448          | 0.1396 |
+### Framework versions
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1