<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
distilBERT_token_itr0_1e-05_essays_01_03_2022-15_11_44
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: 0.3082
- Precision: 0.2796
- Recall: 0.4373
- F1: 0.3411
- Accuracy: 0.8887
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 | 11 | 0.5018 | 0.0192 | 0.0060 | 0.0091 | 0.7370 |
| No log | 2.0 | 22 | 0.4066 | 0.1541 | 0.2814 | 0.1992 | 0.8340 |
| No log | 3.0 | 33 | 0.3525 | 0.1768 | 0.3234 | 0.2286 | 0.8612 |
| No log | 4.0 | 44 | 0.3250 | 0.2171 | 0.3503 | 0.2680 | 0.8766 |
| No log | 5.0 | 55 | 0.3160 | 0.2353 | 0.3713 | 0.2880 | 0.8801 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.1+cu113
- Datasets 1.18.0
- Tokenizers 0.10.3
