Commit
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bbaeb34
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Parent(s):
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End of training
Browse files- README.md +74 -0
- logs/events.out.tfevents.1714041825.c8da74d38726.346.0 +2 -2
- model.safetensors +1 -1
README.md
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---
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license: apache-2.0
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base_model: projecte-aina/roberta-base-ca-v2-cased-te
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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: 2504v4-8ep
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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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# 2504v4-8ep
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This model is a fine-tuned version of [projecte-aina/roberta-base-ca-v2-cased-te](https://huggingface.co/projecte-aina/roberta-base-ca-v2-cased-te) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5711
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- Accuracy: 0.8487
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- Precision: 0.8523
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- Recall: 0.8487
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- F1: 0.8484
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- Ratio: 0.5504
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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: 16
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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: 32
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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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- lr_scheduler_warmup_ratio: 0.06
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- num_epochs: 4
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- label_smoothing_factor: 0.1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Ratio |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
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| 2.0709 | 0.9870 | 38 | 0.8049 | 0.7059 | 0.7073 | 0.7059 | 0.7054 | 0.4580 |
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| 0.7325 | 2.0 | 77 | 0.6190 | 0.8067 | 0.8081 | 0.8067 | 0.8065 | 0.5336 |
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| 0.6249 | 2.9870 | 115 | 0.5998 | 0.8109 | 0.8230 | 0.8109 | 0.8091 | 0.5966 |
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| 0.5768 | 3.9481 | 152 | 0.5711 | 0.8487 | 0.8523 | 0.8487 | 0.8484 | 0.5504 |
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### Framework versions
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- Transformers 4.40.0
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- Pytorch 2.2.1+cu121
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- Datasets 2.19.0
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- Tokenizers 0.19.1
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logs/events.out.tfevents.1714041825.c8da74d38726.346.0
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model.safetensors
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