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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-3-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: 0.05841094794583167
---

<!-- 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-3-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: 2.3008
- Accuracy: 0.0584

## 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: 3.0

### 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          | 0.0526   |
| 2.7004        | 0.17  | 5    | 2.5078          | 0.0529   |
| 2.5681        | 0.21  | 6    | 2.4941          | 0.0532   |
| 2.6404        | 0.24  | 7    | 2.4883          | 0.0534   |
| 2.5325        | 0.28  | 8    | 2.4805          | 0.0536   |
| 2.7205        | 0.31  | 9    | 2.4746          | 0.0536   |
| 2.5149        | 0.34  | 10   | 2.4648          | 0.0533   |
| 2.5017        | 0.38  | 11   | 2.4512          | 0.0535   |
| 2.7026        | 0.41  | 12   | 2.4395          | 0.0539   |
| 2.5259        | 0.45  | 13   | 2.4316          | 0.0543   |
| 2.563         | 0.48  | 14   | 2.4219          | 0.0546   |
| 2.5679        | 0.52  | 15   | 2.4141          | 0.0550   |
| 2.3701        | 0.55  | 16   | 2.4082          | 0.0551   |
| 2.4739        | 0.59  | 17   | 2.4082          | 0.0551   |
| 2.481         | 0.62  | 18   | 2.4023          | 0.0548   |
| 2.5795        | 0.66  | 19   | 2.3945          | 0.0549   |
| 2.4902        | 0.69  | 20   | 2.3867          | 0.0549   |
| 2.4509        | 0.72  | 21   | 2.3809          | 0.0551   |
| 2.6052        | 0.76  | 22   | 2.3730          | 0.0553   |
| 2.3323        | 0.79  | 23   | 2.3633          | 0.0555   |
| 2.5994        | 0.83  | 24   | 2.3555          | 0.0556   |
| 2.3347        | 0.86  | 25   | 2.3477          | 0.0556   |
| 2.421         | 0.9   | 26   | 2.3398          | 0.0559   |
| 2.5337        | 0.93  | 27   | 2.3359          | 0.0560   |
| 2.4102        | 0.97  | 28   | 2.3320          | 0.0563   |
| 2.4309        | 1.0   | 29   | 2.3262          | 0.0564   |
| 1.9305        | 1.03  | 30   | 2.3223          | 0.0564   |
| 1.8601        | 1.07  | 31   | 2.3203          | 0.0567   |
| 1.8682        | 1.1   | 32   | 2.3281          | 0.0564   |
| 1.8657        | 1.14  | 33   | 2.3535          | 0.0564   |
| 2.063         | 1.17  | 34   | 2.3398          | 0.0567   |
| 1.6443        | 1.21  | 35   | 2.3242          | 0.0568   |
| 1.7592        | 1.24  | 36   | 2.3164          | 0.0569   |
| 1.8981        | 1.28  | 37   | 2.3105          | 0.0569   |
| 1.9379        | 1.31  | 38   | 2.3047          | 0.0573   |
| 1.6008        | 1.34  | 39   | 2.3027          | 0.0574   |
| 1.595         | 1.38  | 40   | 2.3027          | 0.0575   |
| 1.7096        | 1.41  | 41   | 2.3027          | 0.0575   |
| 1.7245        | 1.45  | 42   | 2.3027          | 0.0576   |
| 1.795         | 1.48  | 43   | 2.3008          | 0.0577   |
| 1.7241        | 1.52  | 44   | 2.3008          | 0.0576   |
| 1.6356        | 1.55  | 45   | 2.2988          | 0.0576   |
| 1.77          | 1.59  | 46   | 2.2969          | 0.0576   |
| 1.6675        | 1.62  | 47   | 2.2930          | 0.0577   |
| 1.6929        | 1.66  | 48   | 2.2910          | 0.0577   |
| 1.6635        | 1.69  | 49   | 2.2910          | 0.0576   |
| 1.6093        | 1.72  | 50   | 2.2910          | 0.0578   |
| 1.7362        | 1.76  | 51   | 2.2891          | 0.0580   |
| 1.7015        | 1.79  | 52   | 2.2852          | 0.0581   |
| 1.9515        | 1.83  | 53   | 2.2812          | 0.0582   |
| 1.6494        | 1.86  | 54   | 2.2773          | 0.0580   |
| 1.7522        | 1.9   | 55   | 2.2734          | 0.0580   |
| 1.7369        | 1.93  | 56   | 2.2676          | 0.0581   |
| 1.6528        | 1.97  | 57   | 2.2637          | 0.0581   |
| 1.51          | 2.0   | 58   | 2.2617          | 0.0583   |
| 1.4579        | 2.03  | 59   | 2.2637          | 0.0585   |
| 1.2645        | 2.07  | 60   | 2.2695          | 0.0585   |
| 1.2424        | 2.1   | 61   | 2.2773          | 0.0584   |
| 1.2117        | 2.14  | 62   | 2.2891          | 0.0584   |
| 1.4059        | 2.17  | 63   | 2.3008          | 0.0580   |
| 1.328         | 2.21  | 64   | 2.3145          | 0.0581   |
| 1.3436        | 2.24  | 65   | 2.3281          | 0.0580   |
| 1.389         | 2.28  | 66   | 2.3379          | 0.0580   |
| 1.2127        | 2.31  | 67   | 2.3398          | 0.0580   |
| 1.3645        | 2.34  | 68   | 2.3418          | 0.0581   |
| 1.3389        | 2.38  | 69   | 2.3379          | 0.0581   |
| 1.2549        | 2.41  | 70   | 2.3320          | 0.0581   |
| 1.2193        | 2.45  | 71   | 2.3281          | 0.0582   |
| 1.3617        | 2.48  | 72   | 2.3223          | 0.0583   |
| 1.2336        | 2.52  | 73   | 2.3184          | 0.0583   |
| 1.179         | 2.55  | 74   | 2.3145          | 0.0583   |
| 1.2468        | 2.59  | 75   | 2.3125          | 0.0583   |
| 1.3325        | 2.62  | 76   | 2.3086          | 0.0583   |
| 1.1471        | 2.66  | 77   | 2.3066          | 0.0583   |
| 1.3123        | 2.69  | 78   | 2.3066          | 0.0583   |
| 1.3285        | 2.72  | 79   | 2.3047          | 0.0585   |
| 1.3232        | 2.76  | 80   | 2.3027          | 0.0584   |
| 1.1228        | 2.79  | 81   | 2.3027          | 0.0584   |
| 1.3524        | 2.83  | 82   | 2.3027          | 0.0584   |
| 1.2042        | 2.86  | 83   | 2.3027          | 0.0583   |
| 1.3588        | 2.9   | 84   | 2.3008          | 0.0583   |
| 1.2982        | 2.93  | 85   | 2.3008          | 0.0584   |
| 1.4373        | 2.97  | 86   | 2.3008          | 0.0585   |
| 1.3562        | 3.0   | 87   | 2.3008          | 0.0584   |


### Framework versions

- Transformers 4.25.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1