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emotional-distilbert-1

Text Classification
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distilbert
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End of training

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  1. README.md +11 -15
  2. model.safetensors +1 -1
  3. runs/Apr07_06-43-17_af6885761448/events.out.tfevents.1712472198.af6885761448.2498.0 +3 -0
  4. 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/distilbert-base-uncased](https://huggingface.co/distilbert/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: 2.2897
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- - Accuracy: 0.4383
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- - F1: 0.4254
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- - Precision: 0.4447
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- - Recall: 0.4383
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  ## Model description
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@@ -55,16 +55,12 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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- | 2.7442 | 1.0 | 276 | 2.6950 | 0.2269 | 0.1976 | 0.3690 | 0.2269 |
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- | 1.3965 | 2.0 | 552 | 2.0834 | 0.4147 | 0.4024 | 0.4449 | 0.4147 |
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- | 0.6057 | 3.0 | 828 | 1.8911 | 0.4083 | 0.3995 | 0.4235 | 0.4083 |
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- | 0.2162 | 4.0 | 1104 | 1.8959 | 0.4292 | 0.4223 | 0.4421 | 0.4292 |
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- | 0.0686 | 5.0 | 1380 | 2.0052 | 0.4428 | 0.4246 | 0.4514 | 0.4428 |
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- | 0.0243 | 6.0 | 1656 | 2.1381 | 0.4492 | 0.4336 | 0.4658 | 0.4492 |
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- | 0.0128 | 7.0 | 1932 | 2.2092 | 0.4428 | 0.4261 | 0.4438 | 0.4428 |
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- | 0.0088 | 8.0 | 2208 | 2.2664 | 0.4401 | 0.4256 | 0.4442 | 0.4401 |
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- | 0.0072 | 9.0 | 2484 | 2.2779 | 0.4356 | 0.4244 | 0.4432 | 0.4356 |
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- | 0.0065 | 10.0 | 2760 | 2.2897 | 0.4383 | 0.4254 | 0.4447 | 0.4383 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/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: 2.2137
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+ - Accuracy: 0.4310
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+ - F1: 0.4257
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+ - Precision: 0.4466
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+ - Recall: 0.4310
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 2.7164 | 1.0 | 276 | 2.6348 | 0.2840 | 0.2368 | 0.4033 | 0.2840 |
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+ | 1.3322 | 2.0 | 552 | 2.0566 | 0.4183 | 0.4064 | 0.4338 | 0.4183 |
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+ | 0.5727 | 3.0 | 828 | 1.9395 | 0.4029 | 0.3975 | 0.4292 | 0.4029 |
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+ | 0.2102 | 4.0 | 1104 | 1.9605 | 0.4156 | 0.4115 | 0.4400 | 0.4156 |
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+ | 0.0697 | 5.0 | 1380 | 2.0963 | 0.4365 | 0.4205 | 0.4438 | 0.4365 |
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+ | 0.0261 | 6.0 | 1656 | 2.2137 | 0.4310 | 0.4257 | 0.4466 | 0.4310 |
 
 
 
 
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  ### Framework versions
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