End of training
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- model.safetensors +1 -1
README.md
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---
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license: apache-2.0
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base_model: facebook/wav2vec2-large-xlsr-53
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tags:
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- generated_from_trainer
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model-index:
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- name: nyankole_wav2vec2-runpod-unf
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results: []
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/mbalireshawal-makerere-university/huggingface/runs/f8son95h)
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/mbalireshawal-makerere-university/huggingface/runs/f8son95h)
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/mbalireshawal-makerere-university/huggingface/runs/f8son95h)
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# nyankole_wav2vec2-runpod-unf
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- eval_loss: 0.6801
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- eval_wer: 0.5843
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- eval_runtime: 36.7511
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- eval_samples_per_second: 5.115
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- eval_steps_per_second: 0.653
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- epoch: 28.9976
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- step: 6104
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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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: 4
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 8
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- num_epochs: 100
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- mixed_precision_training: Native AMP
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### Framework versions
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- Transformers 4.42.4
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- Pytorch 2.1.0+cu118
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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