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moctarsmal
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bank-transactions-statements-classification

Text Classification
Transformers
PyTorch
Safetensors
flaubert
Generated from Trainer
Inference Endpoints
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End of training

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  1. README.md +56 -15
  2. pytorch_model.bin +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -17,10 +17,10 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [flaubert/flaubert_small_cased](https://huggingface.co/flaubert/flaubert_small_cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.1580
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- - Accuracy: 0.7403
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- - F1 Macro: 0.7519
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- - F1 Weighted: 0.7311
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  ## Model description
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@@ -45,22 +45,63 @@ The following hyperparameters were used during training:
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  - seed: 42
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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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- - num_epochs: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|
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- | No log | 1.0 | 172 | 3.0068 | 0.2810 | 0.0900 | 0.2272 |
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- | No log | 2.0 | 344 | 2.2030 | 0.4587 | 0.2989 | 0.4108 |
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- | 3.2096 | 3.0 | 516 | 1.7050 | 0.5766 | 0.5069 | 0.5466 |
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- | 3.2096 | 4.0 | 688 | 1.4428 | 0.6538 | 0.6220 | 0.6359 |
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- | 3.2096 | 5.0 | 860 | 1.2683 | 0.7031 | 0.6925 | 0.6899 |
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- | 1.7054 | 6.0 | 1032 | 1.2496 | 0.7164 | 0.7215 | 0.7068 |
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- | 1.7054 | 7.0 | 1204 | 1.2271 | 0.7217 | 0.7316 | 0.7084 |
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- | 1.7054 | 8.0 | 1376 | 1.1727 | 0.7364 | 0.7465 | 0.7273 |
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- | 1.2526 | 9.0 | 1548 | 1.1705 | 0.7410 | 0.7495 | 0.7317 |
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- | 1.2526 | 10.0 | 1720 | 1.1580 | 0.7403 | 0.7519 | 0.7311 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [flaubert/flaubert_small_cased](https://huggingface.co/flaubert/flaubert_small_cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.0458
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+ - Accuracy: 0.7683
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+ - F1 Macro: 0.7945
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+ - F1 Weighted: 0.7635
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  ## Model description
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  - seed: 42
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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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+ - num_epochs: 15
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|
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+ | No log | 0.29 | 50 | 3.6955 | 0.1012 | 0.0238 | 0.0880 |
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+ | No log | 0.58 | 100 | 3.2965 | 0.2150 | 0.0569 | 0.1598 |
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+ | No log | 0.87 | 150 | 3.1122 | 0.2530 | 0.0833 | 0.1889 |
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+ | No log | 1.16 | 200 | 2.6838 | 0.3622 | 0.1800 | 0.3051 |
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+ | No log | 1.45 | 250 | 2.5128 | 0.3808 | 0.1938 | 0.3139 |
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+ | No log | 1.74 | 300 | 2.1573 | 0.4913 | 0.3241 | 0.4522 |
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+ | No log | 2.03 | 350 | 2.0208 | 0.5220 | 0.3910 | 0.4832 |
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+ | No log | 2.33 | 400 | 2.0454 | 0.5053 | 0.4090 | 0.4613 |
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+ | No log | 2.62 | 450 | 1.7601 | 0.5599 | 0.4682 | 0.5303 |
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+ | 3.1338 | 2.91 | 500 | 1.6837 | 0.5965 | 0.5489 | 0.5736 |
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+ | 3.1338 | 3.2 | 550 | 1.6337 | 0.5885 | 0.5744 | 0.5609 |
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+ | 3.1338 | 3.49 | 600 | 1.4553 | 0.6491 | 0.6219 | 0.6322 |
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+ | 3.1338 | 3.78 | 650 | 1.4483 | 0.6531 | 0.6441 | 0.6345 |
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+ | 3.1338 | 4.07 | 700 | 1.4108 | 0.6625 | 0.6810 | 0.6522 |
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+ | 3.1338 | 4.36 | 750 | 1.3241 | 0.6924 | 0.6999 | 0.6769 |
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+ | 3.1338 | 4.65 | 800 | 1.3254 | 0.6824 | 0.6960 | 0.6703 |
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+ | 3.1338 | 4.94 | 850 | 1.3349 | 0.6937 | 0.6952 | 0.6759 |
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+ | 3.1338 | 5.23 | 900 | 1.2264 | 0.7057 | 0.7157 | 0.6931 |
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+ | 3.1338 | 5.52 | 950 | 1.3012 | 0.6891 | 0.7061 | 0.6748 |
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+ | 1.6259 | 5.81 | 1000 | 1.2756 | 0.7071 | 0.7224 | 0.6925 |
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+ | 1.6259 | 6.1 | 1050 | 1.1432 | 0.7317 | 0.7440 | 0.7267 |
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+ | 1.6259 | 6.4 | 1100 | 1.2014 | 0.7290 | 0.7434 | 0.7161 |
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+ | 1.6259 | 6.69 | 1150 | 1.1029 | 0.7483 | 0.7656 | 0.7367 |
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+ | 1.6259 | 6.98 | 1200 | 1.1643 | 0.7310 | 0.7470 | 0.7227 |
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+ | 1.6259 | 7.27 | 1250 | 1.1112 | 0.7477 | 0.7561 | 0.7371 |
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+ | 1.6259 | 7.56 | 1300 | 1.1662 | 0.7350 | 0.7668 | 0.7254 |
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+ | 1.6259 | 7.85 | 1350 | 1.0756 | 0.7577 | 0.7823 | 0.7530 |
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+ | 1.6259 | 8.14 | 1400 | 1.1390 | 0.7403 | 0.7657 | 0.7318 |
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+ | 1.6259 | 8.43 | 1450 | 1.1555 | 0.7437 | 0.7637 | 0.7377 |
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+ | 1.092 | 8.72 | 1500 | 1.1086 | 0.7437 | 0.7686 | 0.7384 |
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+ | 1.092 | 9.01 | 1550 | 1.0789 | 0.7510 | 0.7780 | 0.7427 |
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+ | 1.092 | 9.3 | 1600 | 1.0613 | 0.7543 | 0.7823 | 0.7492 |
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+ | 1.092 | 9.59 | 1650 | 1.0750 | 0.7477 | 0.7701 | 0.7382 |
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+ | 1.092 | 9.88 | 1700 | 1.1412 | 0.7423 | 0.7772 | 0.7349 |
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+ | 1.092 | 10.17 | 1750 | 1.0580 | 0.7617 | 0.7918 | 0.7549 |
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+ | 1.092 | 10.47 | 1800 | 1.0667 | 0.7670 | 0.7856 | 0.7580 |
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+ | 1.092 | 10.76 | 1850 | 1.1344 | 0.7403 | 0.7757 | 0.7332 |
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+ | 1.092 | 11.05 | 1900 | 1.0808 | 0.7603 | 0.7944 | 0.7571 |
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+ | 1.092 | 11.34 | 1950 | 1.0367 | 0.7690 | 0.7932 | 0.7655 |
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+ | 0.9029 | 11.63 | 2000 | 1.0921 | 0.7577 | 0.7861 | 0.7504 |
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+ | 0.9029 | 11.92 | 2050 | 1.0833 | 0.7603 | 0.7912 | 0.7541 |
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+ | 0.9029 | 12.21 | 2100 | 1.0523 | 0.7716 | 0.7968 | 0.7662 |
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+ | 0.9029 | 12.5 | 2150 | 1.0467 | 0.7683 | 0.7939 | 0.7614 |
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+ | 0.9029 | 12.79 | 2200 | 1.0515 | 0.7703 | 0.7987 | 0.7667 |
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+ | 0.9029 | 13.08 | 2250 | 1.0604 | 0.7696 | 0.8020 | 0.7654 |
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+ | 0.9029 | 13.37 | 2300 | 1.0900 | 0.7716 | 0.8002 | 0.7663 |
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+ | 0.9029 | 13.66 | 2350 | 1.0348 | 0.7743 | 0.8009 | 0.7686 |
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+ | 0.9029 | 13.95 | 2400 | 1.0495 | 0.7656 | 0.7929 | 0.7610 |
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+ | 0.9029 | 14.24 | 2450 | 1.0411 | 0.7670 | 0.7956 | 0.7624 |
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+ | 0.7924 | 14.53 | 2500 | 1.0458 | 0.7683 | 0.7945 | 0.7635 |
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+ | 0.7924 | 14.83 | 2550 | 1.0401 | 0.7696 | 0.7982 | 0.7649 |
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  ### Framework versions
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