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billm-mistral-7b-conll03-ner-maxlen-256
WhereIsAI/billm-mistral-7b-conll03-ner-maxlen-256
billm-mistral-7b-conll03-ner-maxlen-256 is a machine learning model from WhereIsAI. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- Access
- Public
- Created
- Jun 14, 2024
- Updated
- Jun 14, 2024
- SHA
- 229d9925
Base models
Datasets
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. -->
billm-mistral-7b-conll03-ner-maxlen-256
This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the conll2003 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2232
- Precision: 0.9277
- Recall: 0.9363
- F1: 0.9320
- Accuracy: 0.9863
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: 0.0001
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0329 | 1.0 | 7021 | 0.1599 | 0.9256 | 0.9357 | 0.9306 | 0.9856 |
| 0.0145 | 2.0 | 14042 | 0.1789 | 0.9312 | 0.9340 | 0.9326 | 0.9860 |
| 0.0106 | 3.0 | 21063 | 0.1931 | 0.9288 | 0.9359 | 0.9324 | 0.9864 |
| 0.0065 | 4.0 | 28084 | 0.2161 | 0.9277 | 0.9361 | 0.9319 | 0.9863 |
| 0.0043 | 5.0 | 35105 | 0.2168 | 0.9276 | 0.9363 | 0.9319 | 0.9864 |
| 0.002 | 6.0 | 42126 | 0.2250 | 0.9274 | 0.9359 | 0.9316 | 0.9863 |
| 0.0027 | 7.0 | 49147 | 0.2246 | 0.9269 | 0.9356 | 0.9312 | 0.9862 |
| 0.0023 | 8.0 | 56168 | 0.2235 | 0.9277 | 0.9364 | 0.9321 | 0.9863 |
| 0.0024 | 9.0 | 63189 | 0.2232 | 0.9276 | 0.9364 | 0.9320 | 0.9863 |
| 0.0016 | 10.0 | 70210 | 0.2232 | 0.9277 | 0.9363 | 0.9320 | 0.9863 |
Framework versions
- PEFT 0.10.0
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
- Library
- peft
- Created
- Jun 14, 2024
- Updated
- Jun 14, 2024