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---
license: other
tags:
- generated_from_trainer
datasets:
- AlekseyKorshuk/dalio-all-io
metrics:
- accuracy
model-index:
- name: dalio-all-io-1.3b
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: AlekseyKorshuk/dalio-all-io
type: AlekseyKorshuk/dalio-all-io
metrics:
- name: Accuracy
type: accuracy
value: 0.05582538140677676
---
<!-- 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. -->
# dalio-all-io-1.3b
This model is a fine-tuned version of [facebook/opt-1.3b](https://huggingface.co/facebook/opt-1.3b) on the AlekseyKorshuk/dalio-all-io dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3652
- Accuracy: 0.0558
## 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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 16
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 1.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.6543 | 0.03 | 1 | 2.6113 | 0.0513 |
| 2.6077 | 0.07 | 2 | 2.6113 | 0.0513 |
| 2.5964 | 0.1 | 3 | 2.5605 | 0.0519 |
| 2.7302 | 0.14 | 4 | 2.5234 | 0.0527 |
| 2.7 | 0.17 | 5 | 2.5078 | 0.0528 |
| 2.5674 | 0.21 | 6 | 2.4941 | 0.0532 |
| 2.6406 | 0.24 | 7 | 2.4883 | 0.0534 |
| 2.5315 | 0.28 | 8 | 2.4805 | 0.0536 |
| 2.7202 | 0.31 | 9 | 2.4727 | 0.0537 |
| 2.5144 | 0.34 | 10 | 2.4648 | 0.0536 |
| 2.4983 | 0.38 | 11 | 2.4512 | 0.0537 |
| 2.7029 | 0.41 | 12 | 2.4414 | 0.0539 |
| 2.5198 | 0.45 | 13 | 2.4336 | 0.0540 |
| 2.5706 | 0.48 | 14 | 2.4258 | 0.0545 |
| 2.5688 | 0.52 | 15 | 2.4180 | 0.0548 |
| 2.3793 | 0.55 | 16 | 2.4102 | 0.0552 |
| 2.4785 | 0.59 | 17 | 2.4043 | 0.0554 |
| 2.4688 | 0.62 | 18 | 2.3984 | 0.0553 |
| 2.5674 | 0.66 | 19 | 2.3984 | 0.0553 |
| 2.5054 | 0.69 | 20 | 2.3945 | 0.0554 |
| 2.452 | 0.72 | 21 | 2.3887 | 0.0555 |
| 2.5999 | 0.76 | 22 | 2.3828 | 0.0556 |
| 2.3665 | 0.79 | 23 | 2.3789 | 0.0556 |
| 2.6223 | 0.83 | 24 | 2.375 | 0.0557 |
| 2.3562 | 0.86 | 25 | 2.3711 | 0.0557 |
| 2.429 | 0.9 | 26 | 2.3691 | 0.0557 |
| 2.563 | 0.93 | 27 | 2.3672 | 0.0558 |
| 2.4573 | 0.97 | 28 | 2.3652 | 0.0558 |
| 2.4883 | 1.0 | 29 | 2.3652 | 0.0558 |
### Framework versions
- Transformers 4.25.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
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