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chenxu0602
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ner_twitter_fine_tune

Token Classification
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distilbert
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Training in progress, epoch 1

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  1. README.md +17 -14
  2. model.safetensors +1 -1
  3. runs/Jun23_01-59-36_MacBook-Pro.local/events.out.tfevents.1719079189.MacBook-Pro.local.63380.0 +2 -2
  4. runs/Jun23_01-59-36_MacBook-Pro.local/events.out.tfevents.1719079399.MacBook-Pro.local.63380.1 +3 -0
  5. runs/Jun23_02-04-15_MacBook-Pro.local/events.out.tfevents.1719079457.MacBook-Pro.local.63380.2 +3 -0
  6. 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-cased](https://huggingface.co/distilbert/distilbert-base-cased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2672
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- - Precision: 0.5759
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- - Recall: 0.5729
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- - F1: 0.5744
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- - Accuracy: 0.9284
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  ## Model description
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@@ -49,23 +49,26 @@ 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: 6
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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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- | No log | 1.0 | 56 | 0.3631 | 0.0 | 0.0 | 0.0 | 0.8760 |
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- | No log | 2.0 | 112 | 0.2937 | 0.4624 | 0.4220 | 0.4413 | 0.9093 |
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- | No log | 3.0 | 168 | 0.2774 | 0.4535 | 0.5266 | 0.4873 | 0.9145 |
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- | No log | 4.0 | 224 | 0.2670 | 0.5183 | 0.5575 | 0.5372 | 0.9223 |
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- | No log | 5.0 | 280 | 0.2605 | 0.5490 | 0.5763 | 0.5623 | 0.9254 |
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- | No log | 6.0 | 336 | 0.2672 | 0.5759 | 0.5729 | 0.5744 | 0.9284 |
 
 
 
 
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  ### Framework versions
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  - Transformers 4.38.2
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- - Pytorch 2.0.0+cu117
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- - Datasets 2.18.0
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  - Tokenizers 0.15.2
 
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  This model is a fine-tuned version of [distilbert/distilbert-base-cased](https://huggingface.co/distilbert/distilbert-base-cased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3312
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+ - Precision: 0.6061
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+ - Recall: 0.5780
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+ - F1: 0.5917
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+ - Accuracy: 0.9289
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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 | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 1.0 | 56 | 0.3419 | 0.4545 | 0.0086 | 0.0168 | 0.8765 |
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+ | No log | 2.0 | 112 | 0.2899 | 0.4802 | 0.4151 | 0.4453 | 0.9108 |
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+ | No log | 3.0 | 168 | 0.2648 | 0.4836 | 0.5557 | 0.5172 | 0.9174 |
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+ | No log | 4.0 | 224 | 0.2758 | 0.6127 | 0.5455 | 0.5771 | 0.9287 |
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+ | No log | 5.0 | 280 | 0.2827 | 0.6183 | 0.5557 | 0.5854 | 0.9289 |
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+ | No log | 6.0 | 336 | 0.2835 | 0.5945 | 0.5935 | 0.5940 | 0.9291 |
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+ | No log | 7.0 | 392 | 0.3128 | 0.6061 | 0.5832 | 0.5944 | 0.9291 |
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+ | No log | 8.0 | 448 | 0.3212 | 0.6182 | 0.5695 | 0.5929 | 0.9291 |
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+ | 0.1652 | 9.0 | 504 | 0.3268 | 0.5969 | 0.5866 | 0.5917 | 0.9281 |
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+ | 0.1652 | 10.0 | 560 | 0.3312 | 0.6061 | 0.5780 | 0.5917 | 0.9289 |
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  ### Framework versions
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  - Transformers 4.38.2
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+ - Pytorch 2.2.0
 
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  - Tokenizers 0.15.2
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