metadata
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: finetuned_twitter_sentiment_LSTM
results: []
finetuned_twitter_sentiment_LSTM
This model is a fine-tuned version of LYTinn/lstm-finetuning-sentiment-model-3000-samples on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9053
- Accuracy: 0.5551
- F1: 0.5509
- Precision: 0.5633
- Recall: 0.5551
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
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.0
- Tokenizers 0.13.2