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M_gpt_v1.1
terzimert/M_gpt_v1.1
M_gpt_v1.1 is a token classification model from terzimert. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Token Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- gpt2
- Access
- Public
- Created
- May 25, 2023
- Updated
- May 25, 2023
- SHA
- cd15487c
Try a prompt
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
M_gpt_v1.1
This model is a fine-tuned version of ai-forever/mGPT on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3792
- Precision: 0.5827
- Recall: 0.3788
- F1: 0.4591
- Accuracy: 0.9070
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.4761 | 1.0 | 882 | 0.3904 | 0.5926 | 0.3282 | 0.4224 | 0.9030 |
| 0.3371 | 2.0 | 1764 | 0.3676 | 0.5491 | 0.3696 | 0.4418 | 0.9033 |
| 0.2884 | 3.0 | 2646 | 0.3792 | 0.5827 | 0.3788 | 0.4591 | 0.9070 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
- Task
- Token Classification
- Library
- transformers
- Type
- gpt2
- License
- apache-2.0
- Created
- May 25, 2023
- Updated
- May 25, 2023