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---
base_model: facebook/bart-large-cnn
library_name: peft
license: mit
tags:
- generated_from_trainer
model-index:
- name: fine_tuned_bart
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. -->
# fine_tuned_bart
This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co./facebook/bart-large-cnn) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7075
## 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: 4e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log | 1.0 | 8 | 0.7205 |
| 0.4729 | 2.0 | 16 | 0.7109 |
| 0.4794 | 3.0 | 24 | 0.7048 |
| 0.4716 | 4.0 | 32 | 0.7081 |
| 0.476 | 5.0 | 40 | 0.7095 |
| 0.476 | 6.0 | 48 | 0.7174 |
| 0.4751 | 7.0 | 56 | 0.7050 |
| 0.4683 | 8.0 | 64 | 0.7047 |
| 0.4583 | 9.0 | 72 | 0.7058 |
| 0.474 | 10.0 | 80 | 0.7045 |
| 0.474 | 11.0 | 88 | 0.7062 |
| 0.4651 | 12.0 | 96 | 0.7047 |
| 0.4523 | 13.0 | 104 | 0.7028 |
| 0.4626 | 14.0 | 112 | 0.7049 |
| 0.4634 | 15.0 | 120 | 0.7067 |
| 0.4634 | 16.0 | 128 | 0.7091 |
| 0.4543 | 17.0 | 136 | 0.7087 |
| 0.4502 | 18.0 | 144 | 0.7084 |
| 0.4604 | 19.0 | 152 | 0.7098 |
| 0.4503 | 20.0 | 160 | 0.7065 |
| 0.4503 | 21.0 | 168 | 0.7046 |
| 0.4642 | 22.0 | 176 | 0.7033 |
| 0.4334 | 23.0 | 184 | 0.7029 |
| 0.4626 | 24.0 | 192 | 0.7037 |
| 0.4584 | 25.0 | 200 | 0.7046 |
| 0.4584 | 26.0 | 208 | 0.7063 |
| 0.4508 | 27.0 | 216 | 0.7075 |
| 0.4498 | 28.0 | 224 | 0.7078 |
| 0.4532 | 29.0 | 232 | 0.7077 |
| 0.4514 | 30.0 | 240 | 0.7075 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |