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---
base_model: jarod0411/zinc10M_gpt2_SMILES_bpe_combined_step1
tags:
- generated_from_trainer
datasets:
- jarod0411/linker_v6
metrics:
- accuracy
model-index:
- name: linker_v6
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: jarod0411/linker_v6
type: jarod0411/linker_v6
metrics:
- name: Accuracy
type: accuracy
value: 0.8994679101285066
---
<!-- 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. -->
# linker_v6
This model is a fine-tuned version of [jarod0411/zinc10M_gpt2_SMILES_bpe_combined_step1](https://huggingface.co/jarod0411/zinc10M_gpt2_SMILES_bpe_combined_step1) on the jarod0411/linker_v6 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3103
- Accuracy: 0.8995
## 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: 16
- eval_batch_size: 16
- seed: 1
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 128
- total_eval_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 0.3747 | 1.0 | 43879 | 0.3539 | 0.8870 |
| 0.3495 | 2.0 | 87758 | 0.3322 | 0.8936 |
| 0.3387 | 3.0 | 131637 | 0.3240 | 0.8959 |
| 0.3322 | 4.0 | 175516 | 0.3194 | 0.8971 |
| 0.3279 | 5.0 | 219395 | 0.3164 | 0.8978 |
| 0.325 | 6.0 | 263274 | 0.3140 | 0.8985 |
| 0.3231 | 7.0 | 307153 | 0.3125 | 0.8989 |
| 0.3213 | 8.0 | 351032 | 0.3114 | 0.8992 |
| 0.3201 | 9.0 | 394911 | 0.3107 | 0.8994 |
| 0.3191 | 10.0 | 438790 | 0.3103 | 0.8995 |
### Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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