metadata

license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
datasets:
  - imdb
metrics:
  - accuracy
model-index:
  - name: left_padding0model
    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: 0.92484

left_padding0model

This model is a fine-tuned version of distilbert-base-uncased on the imdb dataset. It achieves the following results on the evaluation set:

Accuracy: 0.9248
Loss: 0.6918

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: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Accuracy	Validation Loss
0.2227	1.0	1563	0.9217	0.2214
0.1325	2.0	3126	0.9312	0.2340
0.1433	3.0	4689	0.9273	0.2143
0.1093	4.0	6252	0.9267	0.3209
0.0601	5.0	7815	0.9276	0.3734
0.0497	6.0	9378	0.9174	0.4883
0.0632	7.0	10941	0.9169	0.4722
0.0301	8.0	12504	0.9048	0.5964
0.0292	9.0	14067	0.9261	0.4406
0.0119	10.0	15630	0.9264	0.5227
0.0218	11.0	17193	0.9294	0.5665
0.0161	12.0	18756	0.9276	0.5829
0.0068	13.0	20319	0.928	0.5820
0.0265	14.0	21882	0.9229	0.5842
0.0098	15.0	23445	0.9283	0.6034
0.0081	16.0	25008	0.9251	0.6624
0.0062	17.0	26571	0.9138	0.5561
0.0153	18.0	28134	0.9223	0.6722
0.0213	19.0	29697	0.9233	0.6735
0.0148	20.0	31260	0.9283	0.5918
0.0076	21.0	32823	0.9248	0.7200
0.0088	22.0	34386	0.9221	0.6554
0.0072	23.0	35949	0.9248	0.6918

Framework versions

Transformers 4.35.0
Pytorch 2.0.0+cu117
Datasets 2.14.6
Tokenizers 0.14.1