DistilBERT_FINAL_ctxSentence_TRAIN_webDiscourse_TEST_NULL_second_train_set_null_False
This model is a fine-tuned version of distilbert-base-uncased-finetuned-sst-2-english on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.0703
- Precision: 0.9667
- Recall: 0.0505
- F1: 0.0961
- Accuracy: 0.0766
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 95 | 0.5442 | 0.6667 | 0.1132 | 0.1935 | 0.75 |
No log | 2.0 | 190 | 0.5316 | 0.5385 | 0.1321 | 0.2121 | 0.74 |
No log | 3.0 | 285 | 0.5384 | 0.4615 | 0.2264 | 0.3038 | 0.725 |
No log | 4.0 | 380 | 0.5503 | 0.4286 | 0.2264 | 0.2963 | 0.715 |
No log | 5.0 | 475 | 0.5529 | 0.4286 | 0.2264 | 0.2963 | 0.715 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.1+cu113
- Datasets 1.18.0
- Tokenizers 0.10.3
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