File size: 1,964 Bytes
498b646 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 |
---
license: mit
base_model: philschmid/bart-large-cnn-samsum
tags:
- generated_from_trainer
model-index:
- name: bart-model
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. -->
# bart-model
This model is a fine-tuned version of [philschmid/bart-large-cnn-samsum](https://huggingface.co/philschmid/bart-large-cnn-samsum) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6169
## 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: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.487 | 0.8 | 10 | 1.2019 |
| 1.3092 | 1.61 | 20 | 0.9905 |
| 1.0316 | 2.41 | 30 | 0.7841 |
| 0.8111 | 3.22 | 40 | 0.6587 |
| 0.7191 | 4.02 | 50 | 0.5964 |
| 0.5906 | 4.82 | 60 | 0.5613 |
| 0.5351 | 5.63 | 70 | 0.5393 |
| 0.4696 | 6.43 | 80 | 0.5429 |
| 0.4249 | 7.24 | 90 | 0.5287 |
| 0.3619 | 8.04 | 100 | 0.5577 |
| 0.3303 | 8.84 | 110 | 0.5794 |
| 0.2718 | 9.65 | 120 | 0.6169 |
### Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
|