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End of training

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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: facebook/hubert-base-ls960
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: hubert-amharic
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+ results: []
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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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+ [<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/hallo23/huggingface/runs/5pgjd6az)
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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/hallo23/huggingface/runs/5pgjd6az)
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+ # hubert-amharic
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+
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+ This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2717
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+ - Accuracy: 0.9556
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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: 1e-05
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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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: linear
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+ - num_epochs: 15
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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 | Accuracy |
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+ |:-------------:|:-------:|:----:|:---------------:|:--------:|
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+ | 0.5372 | 2.0202 | 500 | 0.3764 | 0.8929 |
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+ | 0.2254 | 4.0404 | 1000 | 0.3798 | 0.9111 |
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+ | 0.1699 | 6.0606 | 1500 | 0.1964 | 0.9535 |
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+ | 0.1245 | 8.0808 | 2000 | 0.2290 | 0.9596 |
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+ | 0.0597 | 10.1010 | 2500 | 0.2243 | 0.9636 |
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+ | 0.0816 | 12.1212 | 3000 | 0.2717 | 0.9556 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.0.dev0
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+ - Pytorch 2.1.2
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+ - Datasets 2.19.1.dev0
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+ - Tokenizers 0.19.1
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