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akashjoy
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distilbert-base-uncased-finetuned-airline-sentiment-tweets

Text Classification
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distilbert
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  1. README.md +14 -9
  2. model.safetensors +1 -1
  3. runs/Mar26_12-11-03_HeX/events.out.tfevents.1711469464.HeX.864.0 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -18,9 +18,9 @@ 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: 0.5670
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- - F1: 0.8522
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- - Accuracy: 0.8645
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  ## Model description
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@@ -45,17 +45,22 @@ 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 | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|
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- | 0.0844 | 1.0 | 37 | 0.4748 | 0.8508 | 0.8696 |
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- | 0.0536 | 2.0 | 74 | 0.5032 | 0.8536 | 0.8645 |
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- | 0.0321 | 3.0 | 111 | 0.4869 | 0.8621 | 0.8628 |
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- | 0.0255 | 4.0 | 148 | 0.5432 | 0.8537 | 0.8645 |
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- | 0.0261 | 5.0 | 185 | 0.5670 | 0.8522 | 0.8645 |
 
 
 
 
 
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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: 0.4263
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+ - F1: 0.8517
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+ - Accuracy: 0.8611
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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: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|
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+ | 0.6941 | 1.0 | 37 | 0.5893 | 0.6562 | 0.7599 |
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+ | 0.4702 | 2.0 | 74 | 0.4036 | 0.8273 | 0.8559 |
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+ | 0.3246 | 3.0 | 111 | 0.3389 | 0.8563 | 0.8645 |
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+ | 0.2341 | 4.0 | 148 | 0.3554 | 0.8518 | 0.8645 |
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+ | 0.1846 | 5.0 | 185 | 0.3678 | 0.8555 | 0.8662 |
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+ | 0.136 | 6.0 | 222 | 0.4012 | 0.8548 | 0.8679 |
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+ | 0.1087 | 7.0 | 259 | 0.3878 | 0.8680 | 0.8748 |
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+ | 0.0876 | 8.0 | 296 | 0.4014 | 0.8641 | 0.8714 |
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+ | 0.0736 | 9.0 | 333 | 0.4162 | 0.8584 | 0.8662 |
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+ | 0.0651 | 10.0 | 370 | 0.4263 | 0.8517 | 0.8611 |
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  ### Framework versions
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