End of training
Browse files- README.md +64 -0
- model.safetensors +1 -1
README.md
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---
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base_model: Fsoft-AIC/videberta-base
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tags:
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- generated_from_trainer
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metrics:
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- f1
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model-index:
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- name: mrc-videnerta-dsc
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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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# mrc-videnerta-dsc
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This model is a fine-tuned version of [Fsoft-AIC/videberta-base](https://huggingface.co/Fsoft-AIC/videberta-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8100
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- Exact Match: 0.5970
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- F1: 0.7653
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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: 2e-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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- num_epochs: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Exact Match | F1 |
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|:-------------:|:-----:|:-----:|:---------------:|:-----------:|:------:|
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| 0.967 | 1.0 | 3098 | 0.8918 | 0.5358 | 0.7128 |
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| 0.8396 | 2.0 | 6196 | 0.8346 | 0.5610 | 0.7488 |
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| 0.7209 | 3.0 | 9294 | 0.8057 | 0.5825 | 0.7624 |
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| 0.6532 | 4.0 | 12392 | 0.8212 | 0.5951 | 0.7513 |
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| 0.601 | 5.0 | 15490 | 0.8100 | 0.5970 | 0.7653 |
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### Framework versions
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- Transformers 4.41.1
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- Pytorch 2.2.1
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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model.safetensors
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size 735049552
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version https://git-lfs.github.com/spec/v1
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size 735049552
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