File size: 5,095 Bytes
9690538 a6c626b 9690538 a6c626b 9690538 a6c626b 9690538 de6439e a6c626b 9690538 de6439e 9690538 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 |
---
license: llama2
base_model: meta-llama/Llama-2-7b-hf
tags:
- generated_from_trainer
datasets:
- tyzhu/lmind_nq_train6000_eval6489_v1_doc_qa_v3
metrics:
- accuracy
model-index:
- name: lmind_nq_train6000_eval6489_v1_doc_qa_v3_3e-5_lora2
results:
- task:
name: Causal Language Modeling
type: text-generation
dataset:
name: tyzhu/lmind_nq_train6000_eval6489_v1_doc_qa_v3
type: tyzhu/lmind_nq_train6000_eval6489_v1_doc_qa_v3
metrics:
- name: Accuracy
type: accuracy
value: 0.5422564102564102
---
<!-- 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. -->
# lmind_nq_train6000_eval6489_v1_doc_qa_v3_3e-5_lora2
This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on the tyzhu/lmind_nq_train6000_eval6489_v1_doc_qa_v3 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0598
- Accuracy: 0.5423
## 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: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 50.0
### Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:-----:|:--------:|:---------------:|
| 1.3948 | 1.0 | 529 | 0.6132 | 1.3087 |
| 1.3789 | 2.0 | 1058 | 0.6146 | 1.2897 |
| 1.3259 | 3.0 | 1587 | 0.6179 | 1.2849 |
| 1.2853 | 4.0 | 2116 | 0.6159 | 1.3169 |
| 1.2556 | 5.0 | 2645 | 0.6132 | 1.3532 |
| 1.1972 | 6.0 | 3174 | 0.6126 | 1.4135 |
| 1.1839 | 7.0 | 3703 | 0.6081 | 1.5007 |
| 1.1334 | 8.0 | 4232 | 0.6074 | 1.5242 |
| 1.0966 | 9.0 | 4761 | 0.5803 | 1.6107 |
| 1.0485 | 10.0 | 5290 | 0.6049 | 1.6749 |
| 1.021 | 11.0 | 5819 | 0.6015 | 1.7324 |
| 0.9918 | 12.0 | 6348 | 0.6007 | 1.7632 |
| 0.947 | 13.0 | 6877 | 0.6011 | 1.8303 |
| 0.9376 | 14.0 | 7406 | 0.5991 | 1.8873 |
| 0.898 | 15.0 | 7935 | 0.5976 | 1.9688 |
| 0.8559 | 16.0 | 8464 | 0.5988 | 1.9724 |
| 0.8348 | 17.0 | 8993 | 0.5714 | 1.9815 |
| 0.8106 | 18.0 | 9522 | 0.598 | 2.0386 |
| 0.7848 | 19.0 | 10051 | 0.5964 | 2.0627 |
| 0.745 | 20.0 | 10580 | 0.5966 | 2.0825 |
| 0.7208 | 21.0 | 11109 | 0.5959 | 2.0959 |
| 0.6842 | 22.0 | 11638 | 0.5968 | 2.1534 |
| 0.6661 | 23.0 | 12167 | 0.5975 | 2.1792 |
| 0.6193 | 24.0 | 12696 | 0.5967 | 2.1530 |
| 0.6064 | 25.0 | 13225 | 0.5958 | 2.1720 |
| 0.5776 | 26.0 | 13754 | 0.5966 | 2.2162 |
| 0.5492 | 27.0 | 14283 | 0.5862 | 2.2382 |
| 0.5256 | 28.0 | 14812 | 0.5963 | 2.2273 |
| 0.5128 | 29.0 | 15341 | 0.5948 | 2.2448 |
| 0.4846 | 30.0 | 15870 | 0.5846 | 2.2697 |
| 0.4623 | 31.0 | 16399 | 0.5968 | 2.2425 |
| 0.4468 | 32.0 | 16928 | 0.5936 | 2.2654 |
| 0.4714 | 33.0 | 17457 | 0.5957 | 2.1317 |
| 0.8308 | 34.0 | 17986 | 0.5973 | 1.9392 |
| 0.6478 | 35.0 | 18515 | 0.5979 | 2.0346 |
| 0.612 | 36.0 | 19044 | 0.5978 | 2.0882 |
| 0.5928 | 37.0 | 19573 | 0.5970 | 2.1420 |
| 0.5698 | 38.0 | 20102 | 0.5966 | 2.1569 |
| 0.5444 | 39.0 | 20631 | 0.5956 | 2.1954 |
| 0.5404 | 40.0 | 21160 | 0.5942 | 2.1724 |
| 0.5124 | 41.0 | 21689 | 0.5939 | 2.2020 |
| 0.5342 | 42.0 | 22218 | 0.5938 | 2.1955 |
| 0.5385 | 43.0 | 22747 | 0.5946 | 2.1431 |
| 0.5673 | 44.0 | 23276 | 0.5948 | 2.1269 |
| 0.7034 | 45.0 | 23805 | 0.5917 | 2.0601 |
| 1.0751 | 46.0 | 24334 | 0.5861 | 1.8910 |
| 1.9072 | 47.0 | 24863 | 0.5518 | 2.1388 |
| 5.2339 | 48.0 | 25392 | 0.3825 | 4.4877 |
| 2.573 | 49.0 | 25921 | 0.5283 | 2.2255 |
| 2.1439 | 50.0 | 26450 | 0.5423 | 2.0598 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.14.1
|