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# lmind_nq_train5000_eval5000_v1_qa_tyzhu_lmind_nq_train5000_eval5000_v1_docidx_gpt2-xl

This model is a fine-tuned version of [tyzhu/lmind_nq_train5000_eval5000_v1_docidx_gpt2-xl](https://huggingface.co/tyzhu/lmind_nq_train5000_eval5000_v1_docidx_gpt2-xl) on the tyzhu/lmind_nq_train5000_eval5000_v1_qa dataset.
It achieves the following results on the evaluation set:
- Loss: 3.0633
- Accuracy: 0.5439

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1904        | 1.0   | 313  | 2.0641          | 0.5571   |
| 1.4563        | 2.0   | 626  | 2.1456          | 0.5555   |
| 0.9724        | 3.0   | 939  | 2.3966          | 0.5538   |
| 0.7466        | 4.0   | 1252 | 2.5222          | 0.5504   |
| 0.6695        | 5.0   | 1565 | 2.5795          | 0.5487   |
| 0.6203        | 6.0   | 1878 | 2.6605          | 0.5505   |
| 0.5896        | 7.0   | 2191 | 2.7405          | 0.5492   |
| 0.5711        | 8.0   | 2504 | 2.7712          | 0.5494   |
| 0.5557        | 9.0   | 2817 | 2.7958          | 0.5491   |
| 0.5441        | 10.0  | 3130 | 2.8280          | 0.5478   |
| 0.5399        | 11.0  | 3443 | 2.8618          | 0.5462   |
| 0.5237        | 12.0  | 3756 | 2.8658          | 0.5464   |
| 0.5215        | 13.0  | 4069 | 2.9267          | 0.5472   |
| 0.5127        | 14.0  | 4382 | 2.9090          | 0.5473   |
| 0.5098        | 15.0  | 4695 | 2.9799          | 0.5452   |
| 0.5015        | 16.0  | 5008 | 3.0038          | 0.5410   |
| 0.4898        | 17.0  | 5321 | 3.0348          | 0.5451   |
| 0.4907        | 18.0  | 5634 | 2.9954          | 0.5439   |
| 0.4744        | 19.0  | 5947 | 3.1094          | 0.5421   |
| 0.4708        | 20.0  | 6260 | 3.0633          | 0.5439   |


### 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_train5000_eval5000_v1_qa"], "metrics": ["accuracy"], "base_model": "tyzhu/lmind_nq_train5000_eval5000_v1_docidx_gpt2-xl", "model-index": [{"name": "lmind_nq_train5000_eval5000_v1_qa_tyzhu_lmind_nq_train5000_eval5000_v1_docidx_gpt2-xl", "results": [{"task": {"type": "text-generation", "name": "Causal Language Modeling"}, "dataset": {"name": "tyzhu/lmind_nq_train5000_eval5000_v1_qa", "type": "tyzhu/lmind_nq_train5000_eval5000_v1_qa"}, "metrics": [{"type": "accuracy", "value": 0.5438564102564103, "name": "Accuracy"}]}]}]}
transformers pytorch gpt2 text-generation generated_from_trainer dataset:tyzhu/lmind_nq_train5000_eval5000_v1_qa base_model:tyzhu/lmind_nq_train5000_eval5000_v1_docidx_gpt2-xl license:mit model-index autotrain_compatible endpoints_compatible text-generation-inference region:us