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---
license: other
tags:
- generated_from_trainer
datasets:
- AlekseyKorshuk/dalio-synthetic-io
metrics:
- accuracy
model-index:
- name: dalio-synthetic-io-1.3b
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: AlekseyKorshuk/dalio-synthetic-io
type: AlekseyKorshuk/dalio-synthetic-io
metrics:
- name: Accuracy
type: accuracy
value: 0.06357949136406908
---
<!-- 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-synthetic-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-synthetic-io dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4961
- Accuracy: 0.0636
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.6941 | 0.05 | 1 | 2.6543 | 0.0622 |
| 2.6914 | 0.11 | 2 | 2.6543 | 0.0622 |
| 2.6003 | 0.16 | 3 | 2.6016 | 0.0627 |
| 2.5603 | 0.21 | 4 | 2.5703 | 0.0626 |
| 2.606 | 0.26 | 5 | 2.5508 | 0.0629 |
| 2.5439 | 0.32 | 6 | 2.5449 | 0.0629 |
| 2.4449 | 0.37 | 7 | 2.5469 | 0.0629 |
| 2.5422 | 0.42 | 8 | 2.5469 | 0.0630 |
| 2.6101 | 0.47 | 9 | 2.5410 | 0.0632 |
| 2.4482 | 0.53 | 10 | 2.5352 | 0.0630 |
| 2.501 | 0.58 | 11 | 2.5293 | 0.0631 |
| 2.5967 | 0.63 | 12 | 2.5215 | 0.0634 |
| 2.4998 | 0.68 | 13 | 2.5137 | 0.0635 |
| 2.5957 | 0.74 | 14 | 2.5098 | 0.0636 |
| 2.5967 | 0.79 | 15 | 2.5039 | 0.0639 |
| 2.5022 | 0.84 | 16 | 2.5 | 0.0637 |
| 2.4314 | 0.89 | 17 | 2.4980 | 0.0637 |
| 2.6279 | 0.95 | 18 | 2.4961 | 0.0636 |
| 2.571 | 1.0 | 19 | 2.4961 | 0.0636 |
### Framework versions
- Transformers 4.25.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
|