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---
library_name: transformers
license: apache-2.0
base_model: allenai/led-base-16384
tags:
- generated_from_trainer
metrics:
- rouge
- bleu
- precision
- recall
- f1
model-index:
- name: LED_sum_approach
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. -->
# LED_sum_approach
This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.3340
- Rouge1: 0.4569
- Rouge2: 0.2272
- Rougel: 0.3918
- Rougelsum: 0.3927
- Gen Len: 20.82
- Bleu: 0.1112
- Precisions: 0.2401
- Brevity Penalty: 0.5852
- Length Ratio: 0.6511
- Translation Length: 795.0
- Reference Length: 1221.0
- Precision: 0.9098
- Recall: 0.8906
- F1: 0.9
- Hashcode: roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.0)
## 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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 | Bleu | Precisions | Brevity Penalty | Length Ratio | Translation Length | Reference Length | Precision | Recall | F1 | Hashcode |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:------:|:----------:|:---------------:|:------------:|:------------------:|:----------------:|:---------:|:------:|:------:|:---------------------------------------------------------:|
| No log | 1.0 | 7 | 7.6476 | 0.348 | 0.1355 | 0.2757 | 0.274 | 21.0 | 0.0602 | 0.1436 | 0.6232 | 0.679 | 829.0 | 1221.0 | 0.8935 | 0.8759 | 0.8845 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.0) |
| No log | 2.0 | 14 | 6.4676 | 0.4218 | 0.2049 | 0.3597 | 0.3592 | 20.94 | 0.1008 | 0.2063 | 0.6419 | 0.6929 | 846.0 | 1221.0 | 0.9027 | 0.8839 | 0.8932 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.0) |
| No log | 3.0 | 21 | 5.0145 | 0.4189 | 0.2067 | 0.362 | 0.3612 | 20.5 | 0.0945 | 0.2152 | 0.5919 | 0.656 | 801.0 | 1221.0 | 0.9087 | 0.8846 | 0.8964 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.0) |
| No log | 4.0 | 28 | 4.2719 | 0.44 | 0.2299 | 0.3791 | 0.3778 | 20.48 | 0.1052 | 0.2337 | 0.5852 | 0.6511 | 795.0 | 1221.0 | 0.9087 | 0.8882 | 0.8982 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.0) |
| No log | 5.0 | 35 | 3.9222 | 0.4538 | 0.238 | 0.3919 | 0.3917 | 20.7 | 0.1062 | 0.2404 | 0.5795 | 0.647 | 790.0 | 1221.0 | 0.9126 | 0.891 | 0.9016 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.0) |
| No log | 6.0 | 42 | 3.6730 | 0.4582 | 0.2266 | 0.3926 | 0.3922 | 20.82 | 0.1093 | 0.236 | 0.5908 | 0.6552 | 800.0 | 1221.0 | 0.9099 | 0.8895 | 0.8995 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.0) |
| No log | 7.0 | 49 | 3.5177 | 0.4639 | 0.2385 | 0.4037 | 0.4033 | 20.76 | 0.117 | 0.2484 | 0.5863 | 0.6519 | 796.0 | 1221.0 | 0.9101 | 0.8901 | 0.8999 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.0) |
| No log | 8.0 | 56 | 3.4234 | 0.4564 | 0.2345 | 0.398 | 0.3978 | 20.72 | 0.1148 | 0.247 | 0.5806 | 0.6478 | 791.0 | 1221.0 | 0.9094 | 0.8891 | 0.899 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.0) |
| No log | 9.0 | 63 | 3.3645 | 0.4518 | 0.2273 | 0.3912 | 0.3913 | 20.82 | 0.1111 | 0.2376 | 0.5886 | 0.6536 | 798.0 | 1221.0 | 0.9087 | 0.8899 | 0.8991 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.0) |
| No log | 10.0 | 70 | 3.3340 | 0.4569 | 0.2272 | 0.3918 | 0.3927 | 20.82 | 0.1112 | 0.2401 | 0.5852 | 0.6511 | 795.0 | 1221.0 | 0.9098 | 0.8906 | 0.9 | roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.0) |
### Framework versions
- Transformers 4.53.0
- Pytorch 2.7.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1
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