metadata
tags:
- generated_from_trainer
base_model: state-spaces/mamba-130m-hf
metrics:
- accuracy
- f1
- recall
- precision
model-index:
- name: mamba-text-classification-v3
results: []
datasets:
- stanfordnlp/imdb
mamba-text-classification
This model is a fine-tuned version of state-spaces/mamba-130m-hf on imdb dataset. It achieves the following results on the evaluation set:
- Loss: 0.3637
- Accuracy: 0.9454
- F1: 0.9454
- Recall: 0.9461
- Precision: 0.9447
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision |
|---|---|---|---|---|---|---|---|
| 0.1731 | 0.9997 | 781 | 0.1553 | 0.9425 | 0.9427 | 0.9462 | 0.9393 |
| 0.1316 | 1.9994 | 1562 | 0.1970 | 0.9319 | 0.9294 | 0.8974 | 0.9639 |
| 0.0224 | 2.9990 | 2343 | 0.3137 | 0.9454 | 0.9455 | 0.9479 | 0.9432 |
| 0.0002 | 4.0 | 3125 | 0.3501 | 0.9449 | 0.9450 | 0.9470 | 0.9431 |
| 0.0004 | 4.9984 | 3905 | 0.3637 | 0.9454 | 0.9454 | 0.9461 | 0.9447 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.2.2+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1