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DIALOGUE_second_model

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End of training

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  1. README.md +54 -10
  2. model.safetensors +1 -1
  3. runs/Jan18_11-26-41_3c59cc46f7a9/events.out.tfevents.1705577210.3c59cc46f7a9.1662.5 +3 -0
  4. runs/Jan18_11-28-37_3c59cc46f7a9/events.out.tfevents.1705577320.3c59cc46f7a9.1662.6 +3 -0
  5. training_args.bin +1 -1
README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1516
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- - Precision: 0.9421
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- - Recall: 0.9342
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- - F1: 0.9313
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- - Accuracy: 0.9342
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  ## Model description
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@@ -49,16 +49,60 @@ 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: 5
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | 0.495 | 1.04 | 50 | 0.0897 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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- | 0.0651 | 2.08 | 100 | 0.0027 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.0666 | 3.12 | 150 | 0.2833 | 0.9149 | 0.9079 | 0.9051 | 0.9079 |
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- | 0.0248 | 4.17 | 200 | 0.1516 | 0.9421 | 0.9342 | 0.9313 | 0.9342 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2252
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+ - Precision: 0.9762
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+ - Recall: 0.9737
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+ - F1: 0.9736
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+ - Accuracy: 0.9737
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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 | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.8806 | 0.31 | 15 | 0.4307 | 0.8746 | 0.8026 | 0.7799 | 0.8026 |
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+ | 0.2694 | 0.62 | 30 | 0.1905 | 0.9421 | 0.9342 | 0.9339 | 0.9342 |
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+ | 0.2452 | 0.94 | 45 | 0.1653 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.1509 | 1.25 | 60 | 0.0549 | 0.9875 | 0.9868 | 0.9868 | 0.9868 |
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+ | 0.1843 | 1.56 | 75 | 0.1065 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.1279 | 1.88 | 90 | 0.3218 | 0.9524 | 0.9474 | 0.9472 | 0.9474 |
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+ | 0.1383 | 2.19 | 105 | 0.2080 | 0.9524 | 0.9474 | 0.9472 | 0.9474 |
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+ | 0.0458 | 2.5 | 120 | 0.1471 | 0.9524 | 0.9474 | 0.9472 | 0.9474 |
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+ | 0.0556 | 2.81 | 135 | 0.1671 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0025 | 3.12 | 150 | 0.1945 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0842 | 3.44 | 165 | 0.2063 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0015 | 3.75 | 180 | 0.2746 | 0.9421 | 0.9342 | 0.9313 | 0.9342 |
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+ | 0.0313 | 4.06 | 195 | 0.0341 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0288 | 4.38 | 210 | 0.1343 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0006 | 4.69 | 225 | 0.1929 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0006 | 5.0 | 240 | 0.2003 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0005 | 5.31 | 255 | 0.2027 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0005 | 5.62 | 270 | 0.2049 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0005 | 5.94 | 285 | 0.2061 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0004 | 6.25 | 300 | 0.2072 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0004 | 6.56 | 315 | 0.2083 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0004 | 6.88 | 330 | 0.2093 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0003 | 7.19 | 345 | 0.2106 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0003 | 7.5 | 360 | 0.2122 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0003 | 7.81 | 375 | 0.2133 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0002 | 8.12 | 390 | 0.2142 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0003 | 8.44 | 405 | 0.2152 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0003 | 8.75 | 420 | 0.2160 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0002 | 9.06 | 435 | 0.2169 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0002 | 9.38 | 450 | 0.2177 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0002 | 9.69 | 465 | 0.2184 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0002 | 10.0 | 480 | 0.2195 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0002 | 10.31 | 495 | 0.2200 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0002 | 10.62 | 510 | 0.2208 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0002 | 10.94 | 525 | 0.2214 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0002 | 11.25 | 540 | 0.2219 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0002 | 11.56 | 555 | 0.2223 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0002 | 11.88 | 570 | 0.2227 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0002 | 12.19 | 585 | 0.2232 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0002 | 12.5 | 600 | 0.2237 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0002 | 12.81 | 615 | 0.2239 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0002 | 13.12 | 630 | 0.2242 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0002 | 13.44 | 645 | 0.2245 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0002 | 13.75 | 660 | 0.2248 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0002 | 14.06 | 675 | 0.2250 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0002 | 14.38 | 690 | 0.2251 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0002 | 14.69 | 705 | 0.2252 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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+ | 0.0002 | 15.0 | 720 | 0.2252 | 0.9762 | 0.9737 | 0.9736 | 0.9737 |
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  ### Framework versions
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