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---
tags:
- generated_from_trainer
datasets:
- gem
model_index:
- name: BART-commongen
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: gem
type: gem
args: common_gen
---
<!-- 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-commongen
This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the gem dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1263
- Spice: 0.4178
## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 6317
### Training results
| Training Loss | Epoch | Step | Validation Loss | Spice |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 9.0971 | 0.05 | 100 | 4.1336 | 0.3218 |
| 3.5348 | 0.09 | 200 | 1.5467 | 0.3678 |
| 1.5099 | 0.14 | 300 | 1.1280 | 0.3821 |
| 1.2395 | 0.19 | 400 | 1.1178 | 0.3917 |
| 1.1827 | 0.24 | 500 | 1.0919 | 0.4086 |
| 1.1545 | 0.28 | 600 | 1.1028 | 0.4035 |
| 1.1363 | 0.33 | 700 | 1.1021 | 0.4187 |
| 1.1156 | 0.38 | 800 | 1.1231 | 0.4103 |
| 1.1077 | 0.43 | 900 | 1.1221 | 0.4117 |
| 1.0964 | 0.47 | 1000 | 1.1169 | 0.4088 |
| 1.0704 | 0.52 | 1100 | 1.1143 | 0.4133 |
| 1.0483 | 0.57 | 1200 | 1.1085 | 0.4058 |
| 1.0556 | 0.62 | 1300 | 1.1059 | 0.4249 |
| 1.0343 | 0.66 | 1400 | 1.0992 | 0.4102 |
| 1.0123 | 0.71 | 1500 | 1.1126 | 0.4104 |
| 1.0108 | 0.76 | 1600 | 1.1140 | 0.4177 |
| 1.005 | 0.81 | 1700 | 1.1264 | 0.4078 |
| 0.9822 | 0.85 | 1800 | 1.1256 | 0.4158 |
| 0.9918 | 0.9 | 1900 | 1.1345 | 0.4118 |
| 0.9664 | 0.95 | 2000 | 1.1087 | 0.4073 |
| 0.9532 | 1.0 | 2100 | 1.1217 | 0.4063 |
| 0.8799 | 1.04 | 2200 | 1.1229 | 0.4115 |
| 0.8665 | 1.09 | 2300 | 1.1263 | 0.4178 |
### Framework versions
- Transformers 4.9.2
- Pytorch 1.9.0+cu102
- Datasets 1.11.1.dev0
- Tokenizers 0.10.3
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