End of training

README.md

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+---
+library_name: transformers
+language:
+- ne
+license: mit
+base_model: facebook/w2v-bert-2.0
+tags:
+- generated_from_trainer
+datasets:
+- kiranpantha/OpenSLR54-Balanced-Nepali
+metrics:
+- wer
+model-index:
+- name: Wave2Vec2-Bert2.0 - Kiran Pantha
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: kiranpantha/OpenSLR54-Balanced-Nepali
+      type: kiranpantha/OpenSLR54-Balanced-Nepali
+      args: 'config: ne, split: train,test'
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.4713430282292558
+---
+
+<!-- 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. -->
+
+# Wave2Vec2-Bert2.0 - Kiran Pantha
+
+This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the kiranpantha/OpenSLR54-Balanced-Nepali dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6944
+- Wer: 0.4713
+- Cer: 0.1205
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 2
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Wer    | Cer    |
+|:-------------:|:------:|:----:|:---------------:|:------:|:------:|
+| 0.0949        | 0.24   | 300  | 0.7135          | 0.4638 | 0.1182 |
+| 0.1365        | 0.48   | 600  | 0.7121          | 0.5203 | 0.1346 |
+| 0.1923        | 0.72   | 900  | 0.6871          | 0.5069 | 0.1266 |
+| 0.1618        | 0.96   | 1200 | 0.6799          | 0.4831 | 0.1232 |
+| 0.1142        | 1.2    | 1500 | 0.7192          | 0.4789 | 0.1251 |
+| 0.1124        | 1.44   | 1800 | 0.6891          | 0.4772 | 0.1215 |
+| 0.1032        | 1.6800 | 2100 | 0.7138          | 0.4821 | 0.1226 |
+| 0.1146        | 1.92   | 2400 | 0.6944          | 0.4713 | 0.1205 |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Datasets 3.0.1
+- Tokenizers 0.19.1