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---
base_model: gpt2
tags:
- generated_from_trainer
model-index:
- name: basho_haiku_gpt2_test
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. -->
# basho_haiku_gpt2_test
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7002
## 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: 1
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.9095 | 0.11 | 100 | 0.6605 |
| 0.6638 | 0.22 | 200 | 0.6303 |
| 0.6456 | 0.33 | 300 | 0.6163 |
| 0.6421 | 0.45 | 400 | 0.6139 |
| 0.6421 | 0.56 | 500 | 0.6069 |
| 0.6182 | 0.67 | 600 | 0.5944 |
| 0.6277 | 0.78 | 700 | 0.5910 |
| 0.6409 | 0.89 | 800 | 0.5878 |
| 0.6047 | 1.0 | 900 | 0.5807 |
| 0.4944 | 1.11 | 1000 | 0.5847 |
| 0.4878 | 1.23 | 1100 | 0.5897 |
| 0.4706 | 1.34 | 1200 | 0.5947 |
| 0.4829 | 1.45 | 1300 | 0.5866 |
| 0.4742 | 1.56 | 1400 | 0.5875 |
| 0.4555 | 1.67 | 1500 | 0.5884 |
| 0.4713 | 1.78 | 1600 | 0.5890 |
| 0.4669 | 1.9 | 1700 | 0.5848 |
| 0.475 | 2.01 | 1800 | 0.5838 |
| 0.3762 | 2.12 | 1900 | 0.6123 |
| 0.3703 | 2.23 | 2000 | 0.6172 |
| 0.3772 | 2.34 | 2100 | 0.6118 |
| 0.3731 | 2.45 | 2200 | 0.6090 |
| 0.3662 | 2.56 | 2300 | 0.6151 |
| 0.3894 | 2.68 | 2400 | 0.6132 |
| 0.3663 | 2.79 | 2500 | 0.6195 |
| 0.368 | 2.9 | 2600 | 0.6163 |
| 0.3735 | 3.01 | 2700 | 0.6191 |
| 0.3006 | 3.12 | 2800 | 0.6518 |
| 0.3071 | 3.23 | 2900 | 0.6603 |
| 0.2898 | 3.34 | 3000 | 0.6629 |
| 0.2986 | 3.46 | 3100 | 0.6648 |
| 0.3107 | 3.57 | 3200 | 0.6558 |
| 0.3064 | 3.68 | 3300 | 0.6568 |
| 0.3052 | 3.79 | 3400 | 0.6633 |
| 0.3069 | 3.9 | 3500 | 0.6626 |
| 0.2872 | 4.01 | 3600 | 0.6641 |
| 0.2711 | 4.12 | 3700 | 0.6848 |
| 0.2584 | 4.24 | 3800 | 0.6944 |
| 0.2606 | 4.35 | 3900 | 0.7007 |
| 0.2538 | 4.46 | 4000 | 0.7029 |
| 0.2481 | 4.57 | 4100 | 0.7014 |
| 0.2466 | 4.68 | 4200 | 0.7006 |
| 0.25 | 4.79 | 4300 | 0.6990 |
| 0.2568 | 4.91 | 4400 | 0.7002 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.0.1+cu117
- Datasets 2.18.0
- Tokenizers 0.15.2
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