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---
library_name: transformers
license: apache-2.0
base_model: BEE-spoke-data/ModernBERT2gpt2-700m-cfg2
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: ModernBERT2gpt2-700m-cfg2-t2t-re_pretrain-small-2048
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. -->
# ModernBERT2gpt2-700m-cfg2-t2t-re_pretrain-small-2048
This model is a fine-tuned version of [BEE-spoke-data/ModernBERT2gpt2-700m-cfg2](https://huggingface.co/BEE-spoke-data/ModernBERT2gpt2-700m-cfg2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2095
- Rouge1: 50.3518
- Rouge2: 33.9831
- Rougel: 46.3741
- Rougelsum: 46.7798
- Gen Len: 30.6
- Num Input Tokens Seen: 515531508
## 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: 8e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 80085
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.PAGED_ADEMAMIX and the args are:
No additional optimizer arguments
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 1.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | Input Tokens Seen |
|:-------------:|:------:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-----------------:|
| 90.1752 | 0.0983 | 1000 | 5.6342 | 16.5561 | 3.2961 | 14.7126 | 14.7712 | 69.32 | 51291360 |
| 65.7669 | 0.1966 | 2000 | 4.0524 | 27.4318 | 11.4034 | 24.5864 | 24.8835 | 41.59 | 102933044 |
| 51.9327 | 0.2948 | 3000 | 3.2430 | 40.1723 | 21.3863 | 36.5277 | 36.8678 | 30.495 | 154351440 |
| 41.8728 | 0.3931 | 4000 | 2.8102 | 43.9268 | 26.793 | 40.1378 | 40.7026 | 30.17 | 205979564 |
| 41.7305 | 0.4914 | 5000 | 2.6100 | 44.4312 | 27.6447 | 40.525 | 40.7945 | 32.985 | 257628708 |
| 41.428 | 0.5897 | 6000 | 2.4841 | 44.7711 | 28.0903 | 40.7346 | 40.9658 | 35.03 | 309218384 |
| 36.5789 | 0.6879 | 7000 | 2.3844 | 44.8011 | 28.0367 | 40.8555 | 41.1516 | 30.805 | 360560352 |
| 36.1657 | 0.7862 | 8000 | 2.3185 | 46.647 | 29.8361 | 42.7361 | 43.0175 | 35.32 | 412353688 |
| 33.1455 | 0.8845 | 9000 | 2.2608 | 48.6856 | 32.331 | 44.6585 | 45.0587 | 36.3 | 463798308 |
| 36.9318 | 0.9828 | 10000 | 2.2095 | 50.3518 | 33.9831 | 46.3741 | 46.7798 | 30.6 | 515531508 |
### Framework versions
- Transformers 4.49.0.dev0
- Pytorch 2.4.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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