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---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: t0-all_tasksv2-m1-t1
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. -->
# t0-all_tasksv2-m1-t1
This model is a fine-tuned version of [bigscience/T0_3B](https://huggingface.co/bigscience/T0_3B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1591
- Train Runtime: 31498.6176
- Train Samples Per Second: 15.232
- Train Steps Per Second: 0.212
- Train Loss: 1.4163
- Train Samples: 239899
- Gen Len: 9.847
## 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: 3
- eval_batch_size: 3
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 3
- total_train_batch_size: 72
- total_eval_batch_size: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Accuracy | F1 | Recall | Precision | Bleu 1 | Bleu 2 | Bleu 3 | Bleu 4 | Rouge L | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:--------:|:-------:|:-------:|:---------:|:------:|:------:|:------:|:------:|:-------:|:-------:|
| 1.5957 | 0.15 | 500 | 1.3177 | 51.7673 | 5.9934 | 51.3052 | 51.4889 | 58.2201 | 58.2201 | 58.2201 | 58.2201 | 0.5452 | 0.0004 | 0.0 | 0.0 | 0.5025 | 6.144 |
| 1.5657 | 0.3 | 1000 | 1.2654 | 56.3471 | 6.2554 | 55.9191 | 56.0106 | 64.5902 | 64.5902 | 64.5902 | 64.5902 | 0.5834 | 0.0005 | 0.0 | 0.0 | 0.5423 | 6.363 |
| 1.4614 | 0.45 | 1500 | 1.2279 | 60.3041 | 6.4454 | 59.881 | 60.0203 | 69.9766 | 69.9766 | 69.9766 | 69.9766 | 0.6223 | 0.0005 | 0.0 | 0.0 | 0.5799 | 6.319 |
| 1.4733 | 0.6 | 2000 | 1.2001 | 63.1864 | 6.4428 | 62.7935 | 63.0146 | 74.192 | 74.192 | 74.192 | 74.192 | 0.6527 | 0.0005 | 0.0001 | 0.0 | 0.6102 | 6.319 |
| 1.3982 | 0.75 | 2500 | 1.1888 | 64.2445 | 6.6019 | 63.8196 | 63.9475 | 75.0351 | 75.0351 | 75.0351 | 75.0351 | 0.6606 | 0.0005 | 0.0001 | 0.0 | 0.6151 | 6.3657 |
| 1.4344 | 0.9 | 3000 | 1.1827 | 63.9356 | 6.7482 | 63.5225 | 63.72 | 74.6136 | 74.6136 | 74.6136 | 74.6136 | 0.6576 | 0.0005 | 0.0001 | 0.0 | 0.6123 | 6.3577 |
| 1.3281 | 1.05 | 3500 | 1.1725 | 65.0553 | 6.6823 | 64.6434 | 64.8219 | 76.2529 | 76.2529 | 76.2529 | 76.2529 | 0.6679 | 0.0005 | 0.0001 | 0.0 | 0.6206 | 6.374 |
| 1.3033 | 1.2 | 4000 | 1.1753 | 64.7545 | 6.5216 | 64.3853 | 64.5344 | 76.1124 | 76.1124 | 76.1124 | 76.1124 | 0.6628 | 0.0005 | 0.0001 | 0.0 | 0.619 | 6.4473 |
| 1.2871 | 1.35 | 4500 | 1.1656 | 65.6713 | 6.7135 | 65.185 | 65.4454 | 77.0023 | 77.0023 | 77.0023 | 77.0023 | 0.6718 | 0.0005 | 0.0001 | 0.0 | 0.6246 | 6.472 |
| 1.3423 | 1.5 | 5000 | 1.1669 | 65.8966 | 6.7928 | 65.5016 | 65.6741 | 77.377 | 77.377 | 77.377 | 77.377 | 0.6772 | 0.0005 | 0.0001 | 0.0 | 0.6288 | 6.36 |
| 1.333 | 1.65 | 5500 | 1.1627 | 65.9726 | 6.7915 | 65.5878 | 65.7582 | 77.4239 | 77.4239 | 77.4239 | 77.4239 | 0.6742 | 0.0005 | 0.0001 | 0.0 | 0.6273 | 6.4767 |
| 1.2749 | 1.8 | 6000 | 1.1591 | 66.5212 | 6.9115 | 66.0695 | 66.3204 | 77.9859 | 77.9859 | 77.9859 | 77.9859 | 0.681 | 0.0006 | 0.0001 | 0.0 | 0.6324 | 6.4403 |
| 1.2891 | 1.95 | 6500 | 1.1571 | 66.2478 | 6.8368 | 65.8198 | 66.0423 | 77.5644 | 77.5644 | 77.5644 | 77.5644 | 0.6778 | 0.0005 | 0.0001 | 0.0 | 0.6298 | 6.4417 |
### Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.3.2
- Tokenizers 0.12.1
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