---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: bert-term-importance-v1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# bert-term-importance-v1

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0024
- Mse: 0.0024
- Rmse: 0.0487

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mse    | Rmse   |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 0.0034        | 1.0   | 675  | 0.0036          | 0.0037 | 0.0605 |
| 0.0028        | 2.0   | 1350 | 0.0028          | 0.0028 | 0.0532 |
| 0.0036        | 3.0   | 2025 | 0.0028          | 0.0028 | 0.0530 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.5.1
- Tokenizers 0.21.0