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mistral-7b-instruct-v0.3-mimic4-adapt-multilabel-classify

Text Generation
Transformers
Safetensors
mistral
Generated from Trainer
conversational
text-generation-inference
4-bit precision
bitsandbytes
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  1. README.md +99 -1
  2. config.json +0 -0
  3. eval_loss_plot.png +0 -0
  4. eval_precision_at_15_plot.png +0 -0
  5. model.safetensors +2 -2
  6. train_loss_plot.png +0 -0
  7. training_args.bin +3 -0
README.md CHANGED
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- Load Mistral-7B from mistralai/Mistral-7B-Instruct-v0.3 and combine with these custom weights.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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: mistralai/Mistral-7B-Instruct-v0.3
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: mistral-7b-instruct-v0.3-mimic4-adapt-multilabel-classify
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+ results: []
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+ ---
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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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+
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+ # mistral-7b-instruct-v0.3-mimic4-adapt-multilabel-classify
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+
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+ This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - F1 Micro: 0.0
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+ - F1 Macro: 0.0
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+ - Precision At 5: 0.2765
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+ - Recall At 5: 0.1167
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+ - Precision At 8: 0.2353
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+ - Recall At 8: 0.1441
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+ - Precision At 15: 0.1627
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+ - Recall At 15: 0.1927
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+ - Rare F1 Micro: 0.0
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+ - Rare F1 Macro: 0.0
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+ - Rare Precision: 0.0
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+ - Rare Recall: 0.0
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+ - Rare Precision At 5: 0.2397
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+ - Rare Recall At 5: 0.1023
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+ - Rare Precision At 8: 0.1967
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+ - Rare Recall At 8: 0.1289
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+ - Rare Precision At 15: 0.1397
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+ - Rare Recall At 15: 0.1722
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+ - Not Rare F1 Micro: 0.5956
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+ - Not Rare F1 Macro: 0.3733
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+ - Not Rare Precision: 0.5956
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+ - Not Rare Recall: 0.5956
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+ - Not Rare Precision At 5: 0.0809
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+ - Not Rare Recall At 5: 0.4044
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+ - Not Rare Precision At 8: 0.0506
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+ - Not Rare Recall At 8: 0.4044
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+ - Not Rare Precision At 15: 0.0270
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+ - Not Rare Recall At 15: 0.4044
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+ - Loss: 0.1031
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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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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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 32
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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_steps: 500
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+ - num_epochs: 10
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | F1 Micro | F1 Macro | Precision At 5 | Recall At 5 | Precision At 8 | Recall At 8 | Precision At 15 | Recall At 15 | Rare F1 Micro | Rare F1 Macro | Rare Precision | Rare Recall | Rare Precision At 5 | Rare Recall At 5 | Rare Precision At 8 | Rare Recall At 8 | Rare Precision At 15 | Rare Recall At 15 | Not Rare F1 Micro | Not Rare F1 Macro | Not Rare Precision | Not Rare Recall | Not Rare Precision At 5 | Not Rare Recall At 5 | Not Rare Precision At 8 | Not Rare Recall At 8 | Not Rare Precision At 15 | Not Rare Recall At 15 | Validation Loss |
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+ |:-------------:|:------:|:----:|:--------:|:--------:|:--------------:|:-----------:|:--------------:|:-----------:|:---------------:|:------------:|:-------------:|:-------------:|:--------------:|:-----------:|:-------------------:|:----------------:|:-------------------:|:----------------:|:--------------------:|:-----------------:|:-----------------:|:-----------------:|:------------------:|:---------------:|:-----------------------:|:--------------------:|:-----------------------:|:--------------------:|:------------------------:|:---------------------:|:---------------:|
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+ | 0.699 | 1.0 | 18 | 0.0 | 0.0 | 0.0588 | 0.0135 | 0.0506 | 0.0182 | 0.0441 | 0.0300 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0559 | 0.0128 | 0.0506 | 0.0183 | 0.0426 | 0.0294 | 0.5956 | 0.3733 | 0.5956 | 0.5956 | 0.0809 | 0.4044 | 0.0506 | 0.4044 | 0.0270 | 0.4044 | 0.2374 |
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+ | 0.1279 | 2.0 | 36 | 0.0 | 0.0 | 0.0529 | 0.0128 | 0.0432 | 0.0164 | 0.0436 | 0.0315 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0515 | 0.0120 | 0.0487 | 0.0188 | 0.0446 | 0.0320 | 0.5956 | 0.3733 | 0.5956 | 0.5956 | 0.0809 | 0.4044 | 0.0506 | 0.4044 | 0.0270 | 0.4044 | 0.1224 |
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+ | 0.1087 | 3.0 | 54 | 0.0 | 0.0 | 0.0588 | 0.0136 | 0.0551 | 0.0206 | 0.0525 | 0.0404 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0632 | 0.0152 | 0.0551 | 0.0210 | 0.0466 | 0.0325 | 0.5956 | 0.3733 | 0.5956 | 0.5956 | 0.0809 | 0.4044 | 0.0506 | 0.4044 | 0.0270 | 0.4044 | 0.1073 |
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+ | 0.1027 | 4.0 | 72 | 0.0 | 0.0 | 0.1485 | 0.0500 | 0.1278 | 0.0666 | 0.1025 | 0.0982 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1162 | 0.0336 | 0.0938 | 0.0423 | 0.0789 | 0.0657 | 0.5956 | 0.3733 | 0.5956 | 0.5956 | 0.0809 | 0.4044 | 0.0506 | 0.4044 | 0.0270 | 0.4044 | 0.1043 |
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+ | 0.0973 | 5.0 | 90 | 0.0 | 0.0 | 0.25 | 0.0952 | 0.2105 | 0.1256 | 0.1505 | 0.1609 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2044 | 0.0795 | 0.1682 | 0.1019 | 0.1299 | 0.1405 | 0.5956 | 0.3733 | 0.5956 | 0.5956 | 0.0809 | 0.4044 | 0.0506 | 0.4044 | 0.0270 | 0.4044 | 0.1041 |
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+ | 0.1023 | 6.0 | 108 | 0.0 | 0.0 | 0.2735 | 0.1098 | 0.2206 | 0.1379 | 0.1637 | 0.1803 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2279 | 0.0975 | 0.1811 | 0.1157 | 0.1417 | 0.1629 | 0.5956 | 0.3733 | 0.5956 | 0.5956 | 0.0809 | 0.4044 | 0.0506 | 0.4044 | 0.0270 | 0.4044 | 0.1036 |
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+ | 0.1027 | 7.0 | 126 | 0.0 | 0.0 | 0.2838 | 0.1165 | 0.2325 | 0.1423 | 0.1588 | 0.1861 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2353 | 0.0997 | 0.1893 | 0.1234 | 0.1387 | 0.1698 | 0.5956 | 0.3733 | 0.5956 | 0.5956 | 0.0809 | 0.4044 | 0.0506 | 0.4044 | 0.0270 | 0.4044 | 0.1038 |
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+ | 0.0994 | 8.0 | 144 | 0.0 | 0.0 | 0.2809 | 0.1176 | 0.2353 | 0.1441 | 0.1583 | 0.1850 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2426 | 0.1042 | 0.1930 | 0.1245 | 0.1382 | 0.1696 | 0.5956 | 0.3733 | 0.5956 | 0.5956 | 0.0809 | 0.4044 | 0.0506 | 0.4044 | 0.0270 | 0.4044 | 0.1033 |
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+ | 0.1019 | 9.0 | 162 | 0.0 | 0.0 | 0.2809 | 0.1179 | 0.2353 | 0.1441 | 0.1618 | 0.1915 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2412 | 0.1026 | 0.1912 | 0.1240 | 0.1412 | 0.1725 | 0.5956 | 0.3733 | 0.5956 | 0.5956 | 0.0809 | 0.4044 | 0.0506 | 0.4044 | 0.0270 | 0.4044 | 0.1035 |
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+ | 0.0961 | 9.4507 | 170 | 0.0 | 0.0 | 0.2765 | 0.1167 | 0.2353 | 0.1441 | 0.1627 | 0.1927 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2397 | 0.1023 | 0.1967 | 0.1289 | 0.1397 | 0.1722 | 0.5956 | 0.3733 | 0.5956 | 0.5956 | 0.0809 | 0.4044 | 0.0506 | 0.4044 | 0.0270 | 0.4044 | 0.1031 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.49.0
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+ - Pytorch 2.6.0
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+ - Datasets 3.6.0
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+ - Tokenizers 0.21.1
config.json CHANGED
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