metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: finetuned-Sentiment-classfication-DistilBert-model
results: []
finetuned-Sentiment-classfication-DistilBert-model
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2764
- Rmse: 0.2925
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 16
Training results
Training Loss | Epoch | Step | Validation Loss | Rmse |
---|---|---|---|---|
0.7292 | 2.72 | 500 | 0.3805 | 0.5119 |
0.1778 | 5.43 | 1000 | 0.2802 | 0.3530 |
0.0487 | 8.15 | 1500 | 0.2764 | 0.2925 |
0.0209 | 10.86 | 2000 | 0.2921 | 0.2860 |
0.0113 | 13.58 | 2500 | 0.3244 | 0.2884 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3