metadata

license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: finetuned_token_3e-05_all_16_02_2022-16_29_13
    results: []

finetuned_token_3e-05_all_16_02_2022-16_29_13

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: 0.1630
Precision: 0.3684
Recall: 0.3714
F1: 0.3699
Accuracy: 0.9482

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: 3e-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	38	0.3339	0.1075	0.2324	0.1470	0.8379
No log	2.0	76	0.3074	0.1589	0.2926	0.2060	0.8489
No log	3.0	114	0.2914	0.2142	0.3278	0.2591	0.8591
No log	4.0	152	0.2983	0.1951	0.3595	0.2529	0.8454
No log	5.0	190	0.2997	0.1851	0.3528	0.2428	0.8487

Framework versions

Transformers 4.15.0
Pytorch 1.10.1+cu113
Datasets 1.18.0
Tokenizers 0.10.3