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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
Model card Files
xet
Community
deb101 commited on
Commit
e569498
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1 Parent(s): aaf7431

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Files changed (6) hide show
  1. README.md +16 -16
  2. eval_loss_plot.png +0 -0
  3. eval_precision_at_15_plot.png +0 -0
  4. model.safetensors +1 -1
  5. train_loss_plot.png +0 -0
  6. training_args.bin +1 -1
README.md CHANGED
@@ -18,22 +18,22 @@ This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.3](https
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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: 0.1324
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- - Recall At 5: 0.0502
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- - Precision At 8: 0.1066
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- - Recall At 8: 0.0676
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  - Precision At 15: 0.0789
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- - Recall At 15: 0.0888
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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: 0.0691
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- - Rare Recall At 5: 0.0306
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- - Rare Precision At 8: 0.0579
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- - Rare Recall At 8: 0.0355
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- - Rare Precision At 15: 0.0539
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- - Rare Recall At 15: 0.0584
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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
@@ -44,7 +44,7 @@ It achieves the following results on the evaluation set:
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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: 0.1049
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  ## Model description
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@@ -79,10 +79,10 @@ The following hyperparameters were used during training:
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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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- | 0.6501 | 1.0 | 18 | 0.0 | 0.0 | 0.0118 | 0.0040 | 0.0202 | 0.0083 | 0.0230 | 0.0186 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0147 | 0.0046 | 0.0184 | 0.0080 | 0.0206 | 0.0178 | 0.5956 | 0.3733 | 0.5956 | 0.5956 | 0.0809 | 0.4044 | 0.0506 | 0.4044 | 0.0270 | 0.4044 | 0.2199 |
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- | 0.124 | 2.0 | 36 | 0.0 | 0.0 | 0.0206 | 0.0065 | 0.0202 | 0.0108 | 0.0186 | 0.0181 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0162 | 0.0070 | 0.0202 | 0.0109 | 0.0216 | 0.0197 | 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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- | 0.1083 | 3.0 | 54 | 0.0 | 0.0 | 0.0382 | 0.0155 | 0.0368 | 0.0233 | 0.0338 | 0.0364 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0382 | 0.0153 | 0.0340 | 0.0203 | 0.0279 | 0.0289 | 0.5956 | 0.3733 | 0.5956 | 0.5956 | 0.0809 | 0.4044 | 0.0506 | 0.4044 | 0.0270 | 0.4044 | 0.1074 |
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- | 0.1035 | 3.7887 | 68 | 0.0 | 0.0 | 0.1324 | 0.0502 | 0.1066 | 0.0676 | 0.0789 | 0.0888 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0691 | 0.0306 | 0.0579 | 0.0355 | 0.0539 | 0.0584 | 0.5956 | 0.3733 | 0.5956 | 0.5956 | 0.0809 | 0.4044 | 0.0506 | 0.4044 | 0.0270 | 0.4044 | 0.1049 |
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  ### Framework versions
 
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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: 0.1412
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+ - Recall At 5: 0.0496
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+ - Precision At 8: 0.1131
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+ - Recall At 8: 0.0628
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  - Precision At 15: 0.0789
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+ - Recall At 15: 0.0847
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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: 0.0838
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+ - Rare Recall At 5: 0.0276
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+ - Rare Precision At 8: 0.0671
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+ - Rare Recall At 8: 0.0390
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+ - Rare Precision At 15: 0.0549
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+ - Rare Recall At 15: 0.0565
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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 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: 0.1050
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  ## Model description
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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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+ | 0.5906 | 1.0 | 18 | 0.0 | 0.0 | 0.0221 | 0.0044 | 0.0239 | 0.0096 | 0.0284 | 0.0217 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0235 | 0.0046 | 0.0276 | 0.0108 | 0.0279 | 0.0217 | 0.5956 | 0.3733 | 0.5956 | 0.5956 | 0.0809 | 0.4044 | 0.0506 | 0.4044 | 0.0270 | 0.4044 | 0.2073 |
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+ | 0.1215 | 2.0 | 36 | 0.0 | 0.0 | 0.0382 | 0.0101 | 0.0358 | 0.0143 | 0.0304 | 0.0256 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0382 | 0.0100 | 0.0331 | 0.0132 | 0.0304 | 0.0269 | 0.5956 | 0.3733 | 0.5956 | 0.5956 | 0.0809 | 0.4044 | 0.0506 | 0.4044 | 0.0270 | 0.4044 | 0.1218 |
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+ | 0.1081 | 3.0 | 54 | 0.0 | 0.0 | 0.0691 | 0.0225 | 0.0561 | 0.0276 | 0.0456 | 0.0394 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0706 | 0.0244 | 0.0561 | 0.0291 | 0.0417 | 0.0370 | 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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+ | 0.1034 | 3.7887 | 68 | 0.0 | 0.0 | 0.1412 | 0.0496 | 0.1131 | 0.0628 | 0.0789 | 0.0847 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0838 | 0.0276 | 0.0671 | 0.0390 | 0.0549 | 0.0565 | 0.5956 | 0.3733 | 0.5956 | 0.5956 | 0.0809 | 0.4044 | 0.0506 | 0.4044 | 0.0270 | 0.4044 | 0.1050 |
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  ### Framework versions
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