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---
library_name: transformers
license: apache-2.0
base_model: pszemraj/tFINE-850m-24x24-v0.4-flan_aug
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: tFINE-850m-24x24-v0.4-flan_aug-infinity-instruct-7m-T2T_en-1024-v5
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. -->
# tFINE-850m-24x24-v0.4-flan_aug-infinity-instruct-7m-T2T_en-1024-v5
This model is a fine-tuned version of [pszemraj/tFINE-850m-24x24-v0.4-flan_aug](https://huggingface.co/pszemraj/tFINE-850m-24x24-v0.4-flan_aug) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1526
- Rouge1: 40.1804
- Rouge2: 23.1008
- Rougel: 32.3484
- Rougelsum: 38.2103
- Gen Len: 422.225
- Num Input Tokens Seen: 421585440
## 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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 776444
- gradient_accumulation_steps: 32
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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 |
|:-------------:|:------:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-----------------:|
| 1.8808 | 0.0807 | 1000 | 1.7883 | 24.1946 | 12.2099 | 20.4185 | 22.251 | 636.465 | 35147692 |
| 1.6545 | 0.1613 | 2000 | 1.5985 | 28.9492 | 15.3233 | 23.871 | 26.9919 | 577.04 | 70510224 |
| 1.5522 | 0.2420 | 3000 | 1.4907 | 30.4033 | 16.1354 | 24.7244 | 28.5037 | 537.77 | 105707144 |
| 1.5059 | 0.3227 | 4000 | 1.4204 | 34.0294 | 19.2608 | 27.9322 | 32.3166 | 522.495 | 140722844 |
| 1.4346 | 0.4034 | 5000 | 1.3636 | 34.4104 | 19.4149 | 28.1022 | 32.7299 | 494.68 | 175639924 |
| 1.3912 | 0.4840 | 6000 | 1.3159 | 36.5059 | 21.2447 | 30.116 | 34.7303 | 469.885 | 210409328 |
| 1.3148 | 0.5647 | 7000 | 1.2807 | 37.0123 | 21.3666 | 30.11 | 35.0891 | 458.28 | 245601908 |
| 1.2859 | 0.6454 | 8000 | 1.2492 | 37.05 | 21.0468 | 29.7988 | 35.1882 | 452.495 | 280866724 |
| 1.298 | 0.7260 | 9000 | 1.2211 | 36.6966 | 20.8189 | 29.7115 | 34.7528 | 464.37 | 316042068 |
| 1.2834 | 0.8067 | 10000 | 1.1979 | 37.7181 | 20.9926 | 30.3857 | 35.8681 | 446.26 | 351056548 |
| 1.2577 | 0.8874 | 11000 | 1.1752 | 39.3539 | 23.0123 | 31.9005 | 37.4941 | 424.445 | 386471860 |
| 1.193 | 0.9680 | 12000 | 1.1526 | 40.1804 | 23.1008 | 32.3484 | 38.2103 | 422.225 | 421585440 |
### Framework versions
- Transformers 4.45.1
- Pytorch 2.4.1+cu124
- Datasets 3.0.1
- Tokenizers 0.20.0
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