animeshjoshi/text_classification_tutorial

1---2license: apache-2.03base_model: distilbert-base-uncased4tags:5- generated_from_trainer6datasets:7- rotten_tomatoes8metrics:9- accuracy10model-index:11- name: text_classification_tutorial12  results:13  - task:14      name: Text Classification15      type: text-classification16    dataset:17      name: rotten_tomatoes18      type: rotten_tomatoes19      config: default20      split: test21      args: default22    metrics:23    - name: Accuracy24      type: accuracy25      value: 0.847091932457786126---27 28<!-- This model card has been generated automatically according to the information the Trainer had access to. You29should probably proofread and complete it, then remove this comment. -->30 31# text_classification_tutorial32 33This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the rotten_tomatoes dataset.34It achieves the following results on the evaluation set:35- Loss: 0.422836- Accuracy: 0.847137 38## Model description39 40More information needed41 42## Intended uses & limitations43 44More information needed45 46## Training and evaluation data47 48More information needed49 50## Training procedure51 52### Training hyperparameters53 54The following hyperparameters were used during training:55- learning_rate: 2e-0556- train_batch_size: 1657- eval_batch_size: 1658- seed: 4259- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-0860- lr_scheduler_type: linear61- num_epochs: 262 63### Training results64 65| Training Loss | Epoch | Step | Validation Loss | Accuracy |66|:-------------:|:-----:|:----:|:---------------:|:--------:|67| 0.4238        | 1.0   | 534  | 0.3782          | 0.8405   |68| 0.2422        | 2.0   | 1068 | 0.4228          | 0.8471   |69 70 71### Framework versions72 73- Transformers 4.35.274- Pytorch 2.1.0+cu12175- Datasets 2.17.076- Tokenizers 0.15.277