File size: 2,136 Bytes
2067301 a9be50b 2067301 |
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 |
---
tags:
- generated_from_trainer
datasets:
- orange_sum
metrics:
- rouge
model-index:
- name: bert2gpt2SUMM-finetuned-mlsum-finetuned-mlorange_sum
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: orange_sum
type: orange_sum
args: abstract
metrics:
- name: Rouge1
type: rouge
value: 24.949
---
<!-- 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. -->
<img src="https://huggingface.co/Chemsseddine/bert2gpt2_med_ml_orange_summ-finetuned_med_sum_new-finetuned_med_sum_new/resolve/main/logobert2gpt2.png" alt="Map of positive probabilities per country." width="200"/>
# bert2gpt2SUMM-finetuned-mlsum-finetuned-mlorange_sum
This model is a fine-tuned version of [Chemsseddine/bert2gpt2SUMM-finetuned-mlsum](https://huggingface.co/Chemsseddine/bert2gpt2SUMM-finetuned-mlsum) on the orange_sum dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1773
- Rouge1: 24.949
- Rouge2: 7.851
- Rougel: 18.1575
- Rougelsum: 18.4114
- Gen Len: 39.7947
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:-------:|:---------:|:-------:|
| 3.5484 | 1.0 | 1338 | 3.1773 | 24.949 | 7.851 | 18.1575 | 18.4114 | 39.7947 |
### Framework versions
- Transformers 4.20.0
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
|