---
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
---

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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/date3k2/text-classification-imdb/runs/x4pjguay)
# mamba-text-classification

This model is a fine-tuned version of [state-spaces/mamba-130m-hf](https://huggingface.co/state-spaces/mamba-130m-hf) on [imdb](https://huggingface.co/datasets/stanfordnlp/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