File size: 2,201 Bytes
7442d6f |
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
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mbart-large-50-pluska-token-sum
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. -->
# mbart-large-50-pluska-token-sum
This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 4.2944
- Rouge1: 16.8143
- Rouge2: 5.2102
- Rougel: 14.3454
- Rougelsum: 14.7355
## 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: 5.6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| No log | 1.0 | 144 | 3.7149 | 17.1082 | 5.3773 | 14.6384 | 14.9023 |
| No log | 2.0 | 288 | 3.4301 | 17.6442 | 5.7235 | 14.9728 | 15.3384 |
| No log | 3.0 | 432 | 3.4951 | 17.491 | 5.5463 | 14.8284 | 15.2035 |
| 2.9135 | 4.0 | 576 | 3.6706 | 17.1471 | 5.3419 | 14.6302 | 14.9667 |
| 2.9135 | 5.0 | 720 | 3.9122 | 16.6979 | 5.1895 | 14.2909 | 14.6367 |
| 2.9135 | 6.0 | 864 | 4.0815 | 16.5961 | 5.1915 | 14.2459 | 14.5916 |
| 2.9135 | 7.0 | 1008 | 4.2448 | 16.7793 | 5.2088 | 14.3515 | 14.7136 |
| 1.0097 | 8.0 | 1152 | 4.2944 | 16.8143 | 5.2102 | 14.3454 | 14.7355 |
### Framework versions
- Transformers 4.27.0
- Pytorch 2.0.0
- Datasets 2.10.1
- Tokenizers 0.13.2
|