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End of training

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README.md ADDED
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+ ---
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+ library_name: transformers
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+ language:
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+ - ne
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+ license: mit
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+ base_model: facebook/w2v-bert-2.0
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - kiranpantha/OpenSLR54-Balanced-Nepali
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: Wave2Vec2-Bert2.0 - Kiran Pantha
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+ results:
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+ - task:
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+ name: Automatic Speech Recognition
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+ type: automatic-speech-recognition
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+ dataset:
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+ name: OpenSLR54
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+ type: kiranpantha/OpenSLR54-Balanced-Nepali
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+ config: default
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+ split: test
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+ args: 'config: ne, split: train,test'
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 0.43070906308450946
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # Wave2Vec2-Bert2.0 - Kiran Pantha
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+
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+ This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the OpenSLR54 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4058
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+ - Wer: 0.4307
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 500
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+ - num_epochs: 2
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 0.7246 | 0.15 | 300 | 0.5189 | 0.5402 |
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+ | 0.6721 | 0.3 | 600 | 0.6084 | 0.5423 |
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+ | 0.6956 | 0.45 | 900 | 0.5712 | 0.5412 |
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+ | 0.6341 | 0.6 | 1200 | 0.4997 | 0.5105 |
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+ | 0.6119 | 0.75 | 1500 | 0.5008 | 0.5148 |
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+ | 0.564 | 0.9 | 1800 | 0.4627 | 0.4793 |
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+ | 0.5416 | 1.05 | 2100 | 0.4767 | 0.4734 |
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+ | 0.4569 | 1.2 | 2400 | 0.4754 | 0.4651 |
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+ | 0.4768 | 1.35 | 2700 | 0.4420 | 0.4702 |
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+ | 0.438 | 1.5 | 3000 | 0.4563 | 0.4614 |
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+ | 0.4337 | 1.65 | 3300 | 0.4290 | 0.4543 |
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+ | 0.447 | 1.8 | 3600 | 0.4081 | 0.4392 |
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+ | 0.4108 | 1.95 | 3900 | 0.4058 | 0.4307 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.45.0.dev0
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+ - Pytorch 2.4.1+cu121
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+ - Datasets 2.21.0
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+ - Tokenizers 0.19.1
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