---
tags:
- generated_from_trainer
model-index:
- name: b2b_cnn_retrain
  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. -->

# b2b_cnn_retrain

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 8.0538
- Rouge2 Precision: 0.0033
- Rouge2 Recall: 0.0089
- Rouge2 Fmeasure: 0.0048

## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- training_steps: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
| 0.587         | 5.0   | 5    | 8.3529          | 0.0              | 0.0           | 0.0             |
| 0.4646        | 10.0  | 10   | 8.1390          | 0.0033           | 0.003         | 0.0031          |
| 0.4335        | 15.0  | 15   | 8.1031          | 0.0              | 0.0           | 0.0             |
| 0.3966        | 20.0  | 20   | 8.1701          | 0.0              | 0.0           | 0.0             |
| 0.3476        | 25.0  | 25   | 8.2264          | 0.0              | 0.0           | 0.0             |
| 0.2928        | 30.0  | 30   | 8.0323          | 0.0029           | 0.017         | 0.0049          |
| 0.244         | 35.0  | 35   | 7.9815          | 0.0024           | 0.0057        | 0.0034          |
| 0.2059        | 40.0  | 40   | 7.9555          | 0.0035           | 0.0114        | 0.0053          |
| 0.1791        | 45.0  | 45   | 8.0112          | 0.0046           | 0.0114        | 0.0066          |
| 0.1637        | 50.0  | 50   | 8.0538          | 0.0033           | 0.0089        | 0.0048          |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1