End of training
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README.md
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---
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library_name: transformers
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license:
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base_model:
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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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- precision
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- recall
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- f1
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model-index:
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- name: model_dialect
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results: []
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# model_dialect
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This model is a fine-tuned version of [
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Accuracy: 0.
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- Precision: 0.8089
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- Recall: 0.8091
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- F1: 0.8082
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate:
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- train_batch_size:
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- eval_batch_size:
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- seed: 42
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- lr_scheduler_type: linear
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### Training results
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| Training Loss | Epoch
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### Framework versions
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- Transformers 4.
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- Pytorch 2.4.0
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- Datasets 3.0.1
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- Tokenizers 0.20.0
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---
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library_name: transformers
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license: apache-2.0
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base_model: facebook/wav2vec2-base
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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: model_dialect
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results: []
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# model_dialect
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8038
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- Accuracy: 0.7113
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 4e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 16
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-------:|:----:|:---------------:|:--------:|
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| 6.4219 | 0.9455 | 13 | 1.5899 | 0.2610 |
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| 6.2904 | 1.9636 | 27 | 1.4556 | 0.4550 |
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| 5.4442 | 2.9818 | 41 | 1.2566 | 0.5219 |
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| 5.0752 | 4.0 | 55 | 1.1670 | 0.5566 |
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| 4.748 | 4.9455 | 68 | 1.0790 | 0.5958 |
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| 4.2202 | 5.9636 | 82 | 1.0372 | 0.6120 |
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| 4.0075 | 6.9818 | 96 | 0.9833 | 0.6397 |
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| 3.5847 | 8.0 | 110 | 0.9311 | 0.6721 |
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| 3.3304 | 8.9455 | 123 | 0.9242 | 0.6420 |
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| 3.2199 | 9.9636 | 137 | 0.8707 | 0.6928 |
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| 2.9659 | 10.9818 | 151 | 0.8680 | 0.6767 |
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| 2.8954 | 12.0 | 165 | 0.8357 | 0.6952 |
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| 2.6402 | 12.9455 | 178 | 0.8325 | 0.7021 |
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| 2.4812 | 13.9636 | 192 | 0.8158 | 0.6998 |
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| 2.4249 | 14.9818 | 206 | 0.8042 | 0.7090 |
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| 2.4249 | 15.1273 | 208 | 0.8038 | 0.7113 |
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### Framework versions
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- Transformers 4.46.0
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- Pytorch 2.4.0
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- Datasets 3.0.1
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- Tokenizers 0.20.0
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runs/Oct27_20-22-49_dd2cd04d617b/events.out.tfevents.1730060571.dd2cd04d617b.23.0
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runs/Oct27_20-22-49_dd2cd04d617b/events.out.tfevents.1730061278.dd2cd04d617b.23.1
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