End of training

README.md

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+---
+library_name: transformers
+language:
+- ne
+license: mit
+base_model: kiranpantha/w2v-bert-2.0-nepali-iteration-test
+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: OpenSLR54
+      type: kiranpantha/OpenSLR54-Balanced-Nepali
+      config: default
+      split: test
+      args: 'config: ne, split: train,test'
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.4636116306750553
+---
+
+<!-- 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 [kiranpantha/w2v-bert-2.0-nepali-iteration-test](https://huggingface.co/kiranpantha/w2v-bert-2.0-nepali-iteration-test) on the OpenSLR54 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4545
+- Wer: 0.4636
+
+## 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    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 0.392         | 0.15  | 300  | 0.4561          | 0.4579 |
+| 0.5077        | 0.3   | 600  | 0.5402          | 0.5145 |
+| 0.5371        | 0.45  | 900  | 0.5083          | 0.4923 |
+| 0.4943        | 0.6   | 1200 | 0.5103          | 0.5147 |
+| 0.5049        | 0.75  | 1500 | 0.4811          | 0.4752 |
+| 0.4809        | 0.9   | 1800 | 0.4751          | 0.4689 |
+| 0.4633        | 1.05  | 2100 | 0.5031          | 0.4883 |
+| 0.3843        | 1.2   | 2400 | 0.4703          | 0.4573 |
+| 0.3753        | 1.35  | 2700 | 0.4542          | 0.4497 |
+| 0.356         | 1.5   | 3000 | 0.4510          | 0.4503 |
+| 0.3668        | 1.65  | 3300 | 0.4591          | 0.4524 |
+| 0.3386        | 1.8   | 3600 | 0.4399          | 0.4459 |
+| 0.3452        | 1.95  | 3900 | 0.4545          | 0.4636 |
+
+
+### Framework versions
+
+- Transformers 4.45.0.dev0
+- Pytorch 2.4.1+cu121
+- Datasets 2.21.0
+- Tokenizers 0.19.1

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