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hubert-agum960-amharic

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Files changed (10) hide show
  1. README.md +69 -0
  2. all_results.json +9 -0
  3. config.json +93 -0
  4. model.safetensors +3 -0
  5. preprocessor_config.json +9 -0
  6. runs/Jun15_12-00-10_4255ba7a45a2/events.out.tfevents.1718452832.4255ba7a45a2.35.0 +3 -0
  7. runs/Jun15_12-02-40_4255ba7a45a2/events.out.tfevents.1718452968.4255ba7a45a2.35.1 +3 -0
  8. train_results.json +9 -0
  9. trainer_state.json +447 -0
  10. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: facebook/hubert-large-ls960-ft
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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-agum960-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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+ # hubert-agum960-amharic
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+
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+ This model is a fine-tuned version of [facebook/hubert-large-ls960-ft](https://huggingface.co/facebook/hubert-large-ls960-ft) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4469
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+ - Accuracy: 0.9260
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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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+ - 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: 5
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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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+ | 1.0337 | 0.1664 | 500 | 0.9555 | 0.6861 |
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+ | 0.5792 | 0.3328 | 1000 | 0.6325 | 0.8535 |
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+ | 0.3656 | 0.4992 | 1500 | 0.5913 | 0.8789 |
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+ | 0.33 | 0.6656 | 2000 | 0.4296 | 0.9118 |
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+ | 0.2212 | 0.8319 | 2500 | 0.4698 | 0.9155 |
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+ | 0.364 | 0.9983 | 3000 | 0.4107 | 0.9133 |
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+ | 0.2371 | 1.1647 | 3500 | 0.5081 | 0.9118 |
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+ | 0.3086 | 1.3311 | 4000 | 0.4347 | 0.9275 |
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+ | 0.1531 | 1.4975 | 4500 | 0.4469 | 0.9260 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.2
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+ - Pytorch 2.1.2
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+ - Datasets 2.19.2
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+ - Tokenizers 0.19.1
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