indukurs/pruned_model

1---2license: apache-2.03base_model: bert-base-uncased4tags:5- generated_from_trainer6datasets:7- imdb8metrics:9- accuracy10- f111model-index:12- name: pruned_model13  results:14  - task:15      name: Text Classification16      type: text-classification17    dataset:18      name: imdb19      type: imdb20      config: plain_text21      split: test22      args: plain_text23    metrics:24    - name: Accuracy25      type: accuracy26      value: 0.927    - name: F128      type: f129      value: 0.930---31 32<!-- This model card has been generated automatically according to the information the Trainer had access to. You33should probably proofread and complete it, then remove this comment. -->34 35# pruned_model36 37This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the imdb dataset.38It achieves the following results on the evaluation set:39- Loss: 0.320440- Accuracy: 0.941- F1: 0.942 43## Model description44 45More information needed46 47## Intended uses & limitations48 49More information needed50 51## Training and evaluation data52 53More information needed54 55## Training procedure56 57### Training hyperparameters58 59The following hyperparameters were used during training:60- learning_rate: 2e-0561- train_batch_size: 1662- eval_batch_size: 1663- seed: 4264- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-0865- lr_scheduler_type: linear66- num_epochs: 267 68### Training results69 70 71 72### Framework versions73 74- Transformers 4.36.0.dev075- Pytorch 2.1.0+cu11876- Datasets 2.15.077- Tokenizers 0.15.078