File size: 2,434 Bytes
150a525 |
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 |
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mymodel_v2_4
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. -->
# mymodel_v2_4
This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1383
- Rouge1: 0.5107
- Rouge2: 0.1818
- Rougel: 0.4557
- Rougelsum: 0.4753
- Gen Len: 19.4327
## 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: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log | 1.0 | 111 | 1.6651 | 1.0836 | 0.9742 | 1.076 | 1.0681 | 19.4 |
| No log | 2.0 | 222 | 1.6632 | 0.5545 | 0.3924 | 0.5312 | 0.5302 | 19.5855 |
| No log | 3.0 | 333 | 1.7607 | 0.7463 | 0.5905 | 0.7663 | 0.7512 | 19.6982 |
| No log | 4.0 | 444 | 1.8583 | 0.8352 | 0.7153 | 0.8546 | 0.8534 | 19.7018 |
| 1.4574 | 5.0 | 555 | 1.9357 | 0.659 | 0.6196 | 0.6745 | 0.6962 | 19.3273 |
| 1.4574 | 6.0 | 666 | 2.0241 | 0.4785 | 0.4545 | 0.4878 | 0.4997 | 19.6036 |
| 1.4574 | 7.0 | 777 | 2.0663 | 0.2327 | 0.1818 | 0.2741 | 0.2741 | 19.2327 |
| 1.4574 | 8.0 | 888 | 2.0969 | 0.3755 | 0.2916 | 0.3915 | 0.3956 | 19.4545 |
| 1.4574 | 9.0 | 999 | 2.1291 | 0.7743 | 0.5592 | 0.7473 | 0.7881 | 19.3964 |
| 0.3529 | 10.0 | 1110 | 2.1383 | 0.5107 | 0.1818 | 0.4557 | 0.4753 | 19.4327 |
### Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
|