File size: 3,173 Bytes
cf06e00 |
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 73 74 75 76 77 78 79 80 81 82 |
---
license: apache-2.0
base_model: facebook/bart-large
tags:
- generated_from_trainer
metrics:
- rouge
- wer
model-index:
- name: bart_bertsum_1024_250_1000
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_bertsum_1024_250_1000
This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0191
- Rouge1: 0.6894
- Rouge2: 0.4262
- Rougel: 0.6274
- Rougelsum: 0.6272
- Wer: 0.4606
- Bleurt: -0.5228
## 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: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Wer | Bleurt |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:------:|:-------:|
| No log | 0.13 | 250 | 1.2589 | 0.6432 | 0.3644 | 0.5764 | 0.5763 | 0.5168 | -0.3132 |
| 2.1861 | 0.27 | 500 | 1.1641 | 0.6562 | 0.3824 | 0.591 | 0.591 | 0.4985 | -0.867 |
| 2.1861 | 0.4 | 750 | 1.1326 | 0.6626 | 0.3917 | 0.5988 | 0.5987 | 0.4904 | -0.5078 |
| 1.2496 | 0.53 | 1000 | 1.1111 | 0.6657 | 0.3958 | 0.6015 | 0.6014 | 0.4859 | -0.484 |
| 1.2496 | 0.66 | 1250 | 1.0959 | 0.6708 | 0.4014 | 0.6052 | 0.6051 | 0.4814 | -0.4774 |
| 1.193 | 0.8 | 1500 | 1.0774 | 0.6724 | 0.4041 | 0.609 | 0.609 | 0.4787 | -0.494 |
| 1.193 | 0.93 | 1750 | 1.0662 | 0.681 | 0.4127 | 0.6177 | 0.6176 | 0.4742 | -0.4464 |
| 1.14 | 1.06 | 2000 | 1.0593 | 0.6795 | 0.4157 | 0.6178 | 0.6177 | 0.4709 | -0.5849 |
| 1.14 | 1.2 | 2250 | 1.0504 | 0.6784 | 0.4158 | 0.6161 | 0.616 | 0.4685 | -0.3624 |
| 1.0439 | 1.33 | 2500 | 1.0427 | 0.6815 | 0.418 | 0.6196 | 0.6195 | 0.4667 | -0.5998 |
| 1.0439 | 1.46 | 2750 | 1.0357 | 0.6833 | 0.4198 | 0.6209 | 0.6207 | 0.465 | -0.6198 |
| 1.045 | 1.6 | 3000 | 1.0286 | 0.6872 | 0.4238 | 0.6251 | 0.6251 | 0.4635 | -0.4564 |
| 1.045 | 1.73 | 3250 | 1.0248 | 0.6829 | 0.4214 | 0.6222 | 0.6221 | 0.4622 | -0.5228 |
| 1.0242 | 1.86 | 3500 | 1.0198 | 0.69 | 0.4273 | 0.6284 | 0.6283 | 0.4601 | -0.4592 |
| 1.0242 | 1.99 | 3750 | 1.0191 | 0.6894 | 0.4262 | 0.6274 | 0.6272 | 0.4606 | -0.5228 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
|