Model save
Browse files
README.md
ADDED
@@ -0,0 +1,83 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
base_model: mistralai/Mistral-7B-Instruct-v0.2
|
3 |
+
datasets:
|
4 |
+
- generator
|
5 |
+
library_name: peft
|
6 |
+
license: apache-2.0
|
7 |
+
tags:
|
8 |
+
- trl
|
9 |
+
- sft
|
10 |
+
- generated_from_trainer
|
11 |
+
model-index:
|
12 |
+
- name: latest_mixtral_AviationQA-Finetune_
|
13 |
+
results: []
|
14 |
+
---
|
15 |
+
|
16 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
17 |
+
should probably proofread and complete it, then remove this comment. -->
|
18 |
+
|
19 |
+
# latest_mixtral_AviationQA-Finetune_
|
20 |
+
|
21 |
+
This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the generator dataset.
|
22 |
+
|
23 |
+
## Model description
|
24 |
+
|
25 |
+
More information needed
|
26 |
+
|
27 |
+
## Intended uses & limitations
|
28 |
+
|
29 |
+
More information needed
|
30 |
+
|
31 |
+
## Training and evaluation data
|
32 |
+
|
33 |
+
More information needed
|
34 |
+
|
35 |
+
## Training procedure
|
36 |
+
|
37 |
+
### Training hyperparameters
|
38 |
+
|
39 |
+
The following hyperparameters were used during training:
|
40 |
+
- learning_rate: 0.0001
|
41 |
+
- train_batch_size: 2
|
42 |
+
- eval_batch_size: 3
|
43 |
+
- seed: 42
|
44 |
+
- gradient_accumulation_steps: 2
|
45 |
+
- total_train_batch_size: 4
|
46 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
47 |
+
- lr_scheduler_type: constant
|
48 |
+
- lr_scheduler_warmup_ratio: 0.03
|
49 |
+
- num_epochs: 30
|
50 |
+
- mixed_precision_training: Native AMP
|
51 |
+
|
52 |
+
### Training results
|
53 |
+
|
54 |
+
|
55 |
+
|
56 |
+
### Framework versions
|
57 |
+
|
58 |
+
- Transformers 4.42.3
|
59 |
+
- Pytorch 2.1.1+cu121
|
60 |
+
- Datasets 2.20.0
|
61 |
+
- Tokenizers 0.19.1
|
62 |
+
## Training procedure
|
63 |
+
|
64 |
+
|
65 |
+
The following `bitsandbytes` quantization config was used during training:
|
66 |
+
- quant_method: QuantizationMethod.BITS_AND_BYTES
|
67 |
+
- _load_in_8bit: False
|
68 |
+
- _load_in_4bit: True
|
69 |
+
- llm_int8_threshold: 6.0
|
70 |
+
- llm_int8_skip_modules: None
|
71 |
+
- llm_int8_enable_fp32_cpu_offload: False
|
72 |
+
- llm_int8_has_fp16_weight: False
|
73 |
+
- bnb_4bit_quant_type: nf4
|
74 |
+
- bnb_4bit_use_double_quant: False
|
75 |
+
- bnb_4bit_compute_dtype: float16
|
76 |
+
- bnb_4bit_quant_storage: uint8
|
77 |
+
- load_in_4bit: True
|
78 |
+
- load_in_8bit: False
|
79 |
+
|
80 |
+
### Framework versions
|
81 |
+
|
82 |
+
|
83 |
+
- PEFT 0.6.2
|