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---
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
model-index:
- name: baseline
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: imdb
type: imdb
config: plain_text
split: test
args: plain_text
metrics:
- name: Accuracy
type: accuracy
value: 0.92088
---
<!-- 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. -->
# baseline
This model is a fine-tuned version of [textattack/bert-base-uncased-imdb](https://huggingface.co/textattack/bert-base-uncased-imdb) on the imdb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5238
- Accuracy: 0.9209
## 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: 5e-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: 3.0
- mixed_precision_training: Native AMP
### Training script
```bash
python run_glue.py \
--model_name_or_path textattack/bert-base-uncased-imdb \
--dataset_name imdb \
--do_train \
--do_eval \
--max_seq_length 384 \
--pad_to_max_length False \
--per_device_train_batch_size 32 \
--per_device_eval_batch_size 32 \
--fp16 \
--learning_rate 5e-5 \
--optim adamw_torch \
--num_train_epochs 3 \
--overwrite_output_dir \
--output_dir /tmp/bert-base-uncased-imdb
```
### Framework versions
- Transformers 4.27.4
- Pytorch 1.13.1
- Datasets 2.11.0
- Tokenizers 0.13.3
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