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# lmind_nq_train600_eval300_v1_recite_qa_gpt2-xl_1e-4

This model is a fine-tuned version of [gpt2-xl](https://huggingface.co/gpt2-xl) on the tyzhu/lmind_nq_train600_eval300_v1_recite_qa dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3982
- Accuracy: 0.8390

## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 20.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0096        | 1.0   | 93   | 1.3802          | 0.6793   |
| 0.7666        | 2.0   | 186  | 0.6686          | 0.7849   |
| 0.31          | 3.0   | 279  | 0.4719          | 0.8184   |
| 0.1608        | 4.0   | 372  | 0.4038          | 0.8311   |
| 0.1101        | 5.0   | 465  | 0.3742          | 0.8372   |
| 0.0839        | 6.0   | 558  | 0.3734          | 0.8393   |
| 0.0743        | 7.0   | 651  | 0.3625          | 0.8404   |
| 0.0756        | 8.0   | 744  | 0.3654          | 0.8399   |
| 0.0694        | 9.0   | 837  | 0.3742          | 0.8400   |
| 0.0669        | 10.0  | 930  | 0.3712          | 0.8403   |
| 0.0692        | 11.0  | 1023 | 0.3812          | 0.8397   |
| 0.0717        | 12.0  | 1116 | 0.3797          | 0.8395   |
| 0.0762        | 13.0  | 1209 | 0.3892          | 0.8393   |
| 0.0823        | 14.0  | 1302 | 0.3993          | 0.8384   |
| 0.0789        | 15.0  | 1395 | 0.3946          | 0.8389   |
| 0.0737        | 16.0  | 1488 | 0.3927          | 0.8393   |
| 0.0739        | 17.0  | 1581 | 0.3977          | 0.8381   |
| 0.0741        | 18.0  | 1674 | 0.4060          | 0.8379   |
| 0.0741        | 19.0  | 1767 | 0.4047          | 0.8389   |
| 0.0715        | 20.0  | 1860 | 0.3982          | 0.8390   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["tyzhu/lmind_nq_train600_eval300_v1_recite_qa"], "metrics": ["accuracy"], "base_model": "gpt2-xl", "model-index": [{"name": "lmind_nq_train600_eval300_v1_recite_qa_gpt2-xl_1e-4", "results": [{"task": {"type": "text-generation", "name": "Causal Language Modeling"}, "dataset": {"name": "tyzhu/lmind_nq_train600_eval300_v1_recite_qa", "type": "tyzhu/lmind_nq_train600_eval300_v1_recite_qa"}, "metrics": [{"type": "accuracy", "value": 0.8390196078431372, "name": "Accuracy"}]}]}]}
transformers pytorch gpt2 text-generation generated_from_trainer dataset:tyzhu/lmind_nq_train600_eval300_v1_recite_qa base_model:gpt2-xl license:mit model-index autotrain_compatible endpoints_compatible text-generation-inference region:us