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---
license: apache-2.0
tags:
- generated_from_trainer
base_model: facebook/bart-large
model-index:
- name: bart-finetuned-lyrlen-512
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-finetuned-lyrlen-512
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: 1.7206
## 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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 2.221 | 0.04 | 500 | 1.9667 |
| 2.0336 | 0.08 | 1000 | 1.8762 |
| 1.9563 | 0.12 | 1500 | 1.8565 |
| 1.9555 | 0.17 | 2000 | 1.8392 |
| 1.9072 | 0.21 | 2500 | 1.8214 |
| 1.8796 | 0.25 | 3000 | 1.8246 |
| 1.8955 | 0.29 | 3500 | 1.8050 |
| 1.8254 | 0.33 | 4000 | 1.8069 |
| 1.8518 | 0.38 | 4500 | 1.7873 |
| 1.8471 | 0.42 | 5000 | 1.7880 |
| 1.8536 | 0.46 | 5500 | 1.7736 |
| 1.8075 | 0.5 | 6000 | 1.7772 |
| 1.8143 | 0.54 | 6500 | 1.7724 |
| 1.8383 | 0.58 | 7000 | 1.7670 |
| 1.746 | 0.62 | 7500 | 1.7741 |
| 1.7844 | 0.67 | 8000 | 1.7608 |
| 1.7761 | 0.71 | 8500 | 1.7680 |
| 1.7367 | 0.75 | 9000 | 1.7555 |
| 1.7656 | 0.79 | 9500 | 1.7508 |
| 1.7467 | 0.83 | 10000 | 1.7558 |
| 1.7744 | 0.88 | 10500 | 1.7449 |
| 1.7513 | 0.92 | 11000 | 1.7462 |
| 1.7482 | 0.96 | 11500 | 1.7576 |
| 1.724 | 1.0 | 12000 | 1.7525 |
| 1.7043 | 1.04 | 12500 | 1.7746 |
| 1.6869 | 1.08 | 13000 | 1.7531 |
| 1.7405 | 1.12 | 13500 | 1.7473 |
| 1.7343 | 1.17 | 14000 | 1.7396 |
| 1.649 | 1.21 | 14500 | 1.7384 |
| 1.7208 | 1.25 | 15000 | 1.7368 |
| 1.6931 | 1.29 | 15500 | 1.7404 |
| 1.5941 | 1.33 | 16000 | 1.8223 |
| 1.6651 | 1.38 | 16500 | 1.7287 |
| 1.6649 | 1.42 | 17000 | 1.7413 |
| 1.7108 | 1.46 | 17500 | 1.7304 |
| 1.713 | 1.5 | 18000 | 1.7263 |
| 1.6866 | 1.54 | 18500 | 1.7139 |
| 1.6461 | 1.58 | 19000 | 1.7221 |
| 1.6886 | 1.62 | 19500 | 1.7159 |
| 1.6511 | 1.67 | 20000 | 1.7302 |
| 1.6626 | 1.71 | 20500 | 1.7182 |
| 1.7052 | 1.75 | 21000 | 1.7163 |
| 1.6831 | 1.79 | 21500 | 1.7168 |
| 1.6057 | 1.83 | 22000 | 1.7151 |
| 1.6761 | 1.88 | 22500 | 1.7117 |
| 1.6668 | 1.92 | 23000 | 1.7164 |
| 1.612 | 1.96 | 23500 | 1.7122 |
| 1.6617 | 2.0 | 24000 | 1.7131 |
| 1.641 | 2.04 | 24500 | 1.7277 |
| 1.6595 | 2.08 | 25000 | 1.7289 |
| 1.6723 | 2.12 | 25500 | 1.7192 |
| 1.6347 | 2.17 | 26000 | 1.7259 |
| 1.6684 | 2.21 | 26500 | 1.7211 |
| 1.6098 | 2.25 | 27000 | 1.7316 |
| 1.6025 | 2.29 | 27500 | 1.7213 |
| 1.5567 | 2.33 | 28000 | 1.7238 |
| 1.6564 | 2.38 | 28500 | 1.7185 |
| 1.7078 | 2.42 | 29000 | 1.7393 |
| 1.6308 | 2.46 | 29500 | 1.7234 |
| 1.6402 | 2.5 | 30000 | 1.7319 |
| 1.6333 | 2.54 | 30500 | 1.7197 |
| 1.6249 | 2.58 | 31000 | 1.7298 |
| 1.6366 | 2.62 | 31500 | 1.7235 |
| 1.6245 | 2.67 | 32000 | 1.7289 |
| 1.6044 | 2.71 | 32500 | 1.7160 |
| 1.6095 | 2.75 | 33000 | 1.7172 |
| 1.6621 | 2.79 | 33500 | 1.7210 |
| 1.6883 | 2.83 | 34000 | 1.7169 |
| 1.6449 | 2.88 | 34500 | 1.7155 |
| 1.6439 | 2.92 | 35000 | 1.7201 |
| 1.6358 | 2.96 | 35500 | 1.7188 |
| 1.6033 | 3.0 | 36000 | 1.7206 |
### Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.1.0.dev20230621+cu117
- Datasets 2.18.0
- Tokenizers 0.15.2
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