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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-2-epoch
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: 0.057553854065481976
---
<!-- 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-2-epoch
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: 2.2949
- Accuracy: 0.0576
## 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: 2.0
### 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 |
| 2.7002 | 0.17 | 5 | 2.5078 | 0.0529 |
| 2.5674 | 0.21 | 6 | 2.4941 | 0.0533 |
| 2.6399 | 0.24 | 7 | 2.4883 | 0.0534 |
| 2.533 | 0.28 | 8 | 2.4805 | 0.0536 |
| 2.7202 | 0.31 | 9 | 2.4746 | 0.0536 |
| 2.5137 | 0.34 | 10 | 2.4648 | 0.0534 |
| 2.499 | 0.38 | 11 | 2.4512 | 0.0536 |
| 2.7026 | 0.41 | 12 | 2.4414 | 0.0539 |
| 2.5254 | 0.45 | 13 | 2.4336 | 0.0543 |
| 2.5667 | 0.48 | 14 | 2.4238 | 0.0545 |
| 2.5715 | 0.52 | 15 | 2.4160 | 0.0548 |
| 2.3739 | 0.55 | 16 | 2.4102 | 0.0550 |
| 2.4756 | 0.59 | 17 | 2.4043 | 0.0549 |
| 2.4783 | 0.62 | 18 | 2.3984 | 0.0550 |
| 2.5665 | 0.66 | 19 | 2.3906 | 0.0549 |
| 2.4888 | 0.69 | 20 | 2.3906 | 0.0549 |
| 2.4476 | 0.72 | 21 | 2.3828 | 0.0550 |
| 2.604 | 0.76 | 22 | 2.375 | 0.0552 |
| 2.3416 | 0.79 | 23 | 2.3652 | 0.0554 |
| 2.6028 | 0.83 | 24 | 2.3555 | 0.0555 |
| 2.3425 | 0.86 | 25 | 2.3477 | 0.0558 |
| 2.4142 | 0.9 | 26 | 2.3398 | 0.0558 |
| 2.5317 | 0.93 | 27 | 2.3340 | 0.0559 |
| 2.4119 | 0.97 | 28 | 2.3301 | 0.0561 |
| 2.4048 | 1.0 | 29 | 2.3262 | 0.0563 |
| 1.9646 | 1.03 | 30 | 2.3242 | 0.0564 |
| 1.9233 | 1.07 | 31 | 2.3203 | 0.0563 |
| 1.9276 | 1.1 | 32 | 2.3203 | 0.0564 |
| 1.8702 | 1.14 | 33 | 2.3281 | 0.0565 |
| 2.0997 | 1.17 | 34 | 2.3340 | 0.0565 |
| 1.7943 | 1.21 | 35 | 2.3320 | 0.0568 |
| 1.8579 | 1.24 | 36 | 2.3242 | 0.0567 |
| 1.8844 | 1.28 | 37 | 2.3145 | 0.0568 |
| 1.9288 | 1.31 | 38 | 2.3086 | 0.0569 |
| 1.6616 | 1.34 | 39 | 2.3047 | 0.0570 |
| 1.6443 | 1.38 | 40 | 2.3047 | 0.0571 |
| 1.7616 | 1.41 | 41 | 2.3027 | 0.0572 |
| 1.7904 | 1.45 | 42 | 2.3027 | 0.0571 |
| 1.8762 | 1.48 | 43 | 2.3027 | 0.0573 |
| 1.6569 | 1.52 | 44 | 2.3027 | 0.0573 |
| 1.647 | 1.55 | 45 | 2.3027 | 0.0573 |
| 1.8168 | 1.59 | 46 | 2.3027 | 0.0574 |
| 1.7194 | 1.62 | 47 | 2.3027 | 0.0573 |
| 1.7667 | 1.66 | 48 | 2.3027 | 0.0572 |
| 1.7621 | 1.69 | 49 | 2.3027 | 0.0573 |
| 1.7269 | 1.72 | 50 | 2.3008 | 0.0573 |
| 1.7815 | 1.76 | 51 | 2.3008 | 0.0574 |
| 1.8318 | 1.79 | 52 | 2.2988 | 0.0574 |
| 1.9366 | 1.83 | 53 | 2.2988 | 0.0575 |
| 1.736 | 1.86 | 54 | 2.2969 | 0.0576 |
| 1.9984 | 1.9 | 55 | 2.2969 | 0.0575 |
| 1.7203 | 1.93 | 56 | 2.2949 | 0.0575 |
| 1.7391 | 1.97 | 57 | 2.2949 | 0.0576 |
| 1.6611 | 2.0 | 58 | 2.2949 | 0.0576 |
### Framework versions
- Transformers 4.25.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
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