Upload folder using huggingface_hub
Browse files- README.md +204 -0
- adapter_config.json +33 -0
- adapter_model.safetensors +3 -0
- special_tokens_map.json +24 -0
- tokenizer.json +0 -0
- tokenizer_config.json +42 -0
- trainer_state.json +421 -0
- training_args.bin +3 -0
README.md
ADDED
@@ -0,0 +1,204 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
library_name: peft
|
3 |
+
base_model: mistralai/Mistral-7B-v0.1
|
4 |
+
---
|
5 |
+
|
6 |
+
# Model Card for Model ID
|
7 |
+
|
8 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
9 |
+
|
10 |
+
|
11 |
+
|
12 |
+
## Model Details
|
13 |
+
|
14 |
+
### Model Description
|
15 |
+
|
16 |
+
<!-- Provide a longer summary of what this model is. -->
|
17 |
+
|
18 |
+
|
19 |
+
|
20 |
+
- **Developed by:** [More Information Needed]
|
21 |
+
- **Funded by [optional]:** [More Information Needed]
|
22 |
+
- **Shared by [optional]:** [More Information Needed]
|
23 |
+
- **Model type:** [More Information Needed]
|
24 |
+
- **Language(s) (NLP):** [More Information Needed]
|
25 |
+
- **License:** [More Information Needed]
|
26 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
27 |
+
|
28 |
+
### Model Sources [optional]
|
29 |
+
|
30 |
+
<!-- Provide the basic links for the model. -->
|
31 |
+
|
32 |
+
- **Repository:** [More Information Needed]
|
33 |
+
- **Paper [optional]:** [More Information Needed]
|
34 |
+
- **Demo [optional]:** [More Information Needed]
|
35 |
+
|
36 |
+
## Uses
|
37 |
+
|
38 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
39 |
+
|
40 |
+
### Direct Use
|
41 |
+
|
42 |
+
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
43 |
+
|
44 |
+
[More Information Needed]
|
45 |
+
|
46 |
+
### Downstream Use [optional]
|
47 |
+
|
48 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
49 |
+
|
50 |
+
[More Information Needed]
|
51 |
+
|
52 |
+
### Out-of-Scope Use
|
53 |
+
|
54 |
+
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
55 |
+
|
56 |
+
[More Information Needed]
|
57 |
+
|
58 |
+
## Bias, Risks, and Limitations
|
59 |
+
|
60 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
61 |
+
|
62 |
+
[More Information Needed]
|
63 |
+
|
64 |
+
### Recommendations
|
65 |
+
|
66 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
67 |
+
|
68 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
69 |
+
|
70 |
+
## How to Get Started with the Model
|
71 |
+
|
72 |
+
Use the code below to get started with the model.
|
73 |
+
|
74 |
+
[More Information Needed]
|
75 |
+
|
76 |
+
## Training Details
|
77 |
+
|
78 |
+
### Training Data
|
79 |
+
|
80 |
+
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
|
81 |
+
|
82 |
+
[More Information Needed]
|
83 |
+
|
84 |
+
### Training Procedure
|
85 |
+
|
86 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
87 |
+
|
88 |
+
#### Preprocessing [optional]
|
89 |
+
|
90 |
+
[More Information Needed]
|
91 |
+
|
92 |
+
|
93 |
+
#### Training Hyperparameters
|
94 |
+
|
95 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
96 |
+
|
97 |
+
#### Speeds, Sizes, Times [optional]
|
98 |
+
|
99 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
100 |
+
|
101 |
+
[More Information Needed]
|
102 |
+
|
103 |
+
## Evaluation
|
104 |
+
|
105 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
106 |
+
|
107 |
+
### Testing Data, Factors & Metrics
|
108 |
+
|
109 |
+
#### Testing Data
|
110 |
+
|
111 |
+
<!-- This should link to a Dataset Card if possible. -->
|
112 |
+
|
113 |
+
[More Information Needed]
|
114 |
+
|
115 |
+
#### Factors
|
116 |
+
|
117 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
118 |
+
|
119 |
+
[More Information Needed]
|
120 |
+
|
121 |
+
#### Metrics
|
122 |
+
|
123 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
124 |
+
|
125 |
+
[More Information Needed]
|
126 |
+
|
127 |
+
### Results
|
128 |
+
|
129 |
+
[More Information Needed]
|
130 |
+
|
131 |
+
#### Summary
|
132 |
+
|
133 |
+
|
134 |
+
|
135 |
+
## Model Examination [optional]
|
136 |
+
|
137 |
+
<!-- Relevant interpretability work for the model goes here -->
|
138 |
+
|
139 |
+
[More Information Needed]
|
140 |
+
|
141 |
+
## Environmental Impact
|
142 |
+
|
143 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
144 |
+
|
145 |
+
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
146 |
+
|
147 |
+
- **Hardware Type:** [More Information Needed]
|
148 |
+
- **Hours used:** [More Information Needed]
|
149 |
+
- **Cloud Provider:** [More Information Needed]
|
150 |
+
- **Compute Region:** [More Information Needed]
|
151 |
+
- **Carbon Emitted:** [More Information Needed]
|
152 |
+
|
153 |
+
## Technical Specifications [optional]
|
154 |
+
|
155 |
+
### Model Architecture and Objective
|
156 |
+
|
157 |
+
[More Information Needed]
|
158 |
+
|
159 |
+
### Compute Infrastructure
|
160 |
+
|
161 |
+
[More Information Needed]
|
162 |
+
|
163 |
+
#### Hardware
|
164 |
+
|
165 |
+
[More Information Needed]
|
166 |
+
|
167 |
+
#### Software
|
168 |
+
|
169 |
+
[More Information Needed]
|
170 |
+
|
171 |
+
## Citation [optional]
|
172 |
+
|
173 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
174 |
+
|
175 |
+
**BibTeX:**
|
176 |
+
|
177 |
+
[More Information Needed]
|
178 |
+
|
179 |
+
**APA:**
|
180 |
+
|
181 |
+
[More Information Needed]
|
182 |
+
|
183 |
+
## Glossary [optional]
|
184 |
+
|
185 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
186 |
+
|
187 |
+
[More Information Needed]
|
188 |
+
|
189 |
+
## More Information [optional]
|
190 |
+
|
191 |
+
[More Information Needed]
|
192 |
+
|
193 |
+
## Model Card Authors [optional]
|
194 |
+
|
195 |
+
[More Information Needed]
|
196 |
+
|
197 |
+
## Model Card Contact
|
198 |
+
|
199 |
+
[More Information Needed]
|
200 |
+
|
201 |
+
|
202 |
+
### Framework versions
|
203 |
+
|
204 |
+
- PEFT 0.7.1
|
adapter_config.json
ADDED
@@ -0,0 +1,33 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"alpha_pattern": {},
|
3 |
+
"auto_mapping": {
|
4 |
+
"base_model_class": "MistralForCausalLM",
|
5 |
+
"parent_library": "transformers.models.mistral.modeling_mistral"
|
6 |
+
},
|
7 |
+
"base_model_name_or_path": "mistralai/Mistral-7B-v0.1",
|
8 |
+
"bias": "none",
|
9 |
+
"fan_in_fan_out": false,
|
10 |
+
"inference_mode": true,
|
11 |
+
"init_lora_weights": true,
|
12 |
+
"layers_pattern": null,
|
13 |
+
"layers_to_transform": null,
|
14 |
+
"loftq_config": {},
|
15 |
+
"lora_alpha": 8,
|
16 |
+
"lora_dropout": 0.0,
|
17 |
+
"megatron_config": null,
|
18 |
+
"megatron_core": "megatron.core",
|
19 |
+
"modules_to_save": null,
|
20 |
+
"peft_type": "LORA",
|
21 |
+
"r": 8,
|
22 |
+
"rank_pattern": {},
|
23 |
+
"revision": null,
|
24 |
+
"target_modules": [
|
25 |
+
"q_proj",
|
26 |
+
"v_proj",
|
27 |
+
"k_proj",
|
28 |
+
"up_proj",
|
29 |
+
"gate_proj",
|
30 |
+
"down_proj"
|
31 |
+
],
|
32 |
+
"task_type": null
|
33 |
+
}
|
adapter_model.safetensors
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:67c57c4d2b27fafa8a7023bfbb7585492be639407ab02f4e8100646fcbdbafed
|
3 |
+
size 75548136
|
special_tokens_map.json
ADDED
@@ -0,0 +1,24 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"bos_token": {
|
3 |
+
"content": "<s>",
|
4 |
+
"lstrip": false,
|
5 |
+
"normalized": false,
|
6 |
+
"rstrip": false,
|
7 |
+
"single_word": false
|
8 |
+
},
|
9 |
+
"eos_token": {
|
10 |
+
"content": "</s>",
|
11 |
+
"lstrip": false,
|
12 |
+
"normalized": false,
|
13 |
+
"rstrip": false,
|
14 |
+
"single_word": false
|
15 |
+
},
|
16 |
+
"pad_token": "</s>",
|
17 |
+
"unk_token": {
|
18 |
+
"content": "<unk>",
|
19 |
+
"lstrip": false,
|
20 |
+
"normalized": false,
|
21 |
+
"rstrip": false,
|
22 |
+
"single_word": false
|
23 |
+
}
|
24 |
+
}
|
tokenizer.json
ADDED
The diff for this file is too large to render.
See raw diff
|
|
tokenizer_config.json
ADDED
@@ -0,0 +1,42 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"add_bos_token": true,
|
3 |
+
"add_eos_token": false,
|
4 |
+
"added_tokens_decoder": {
|
5 |
+
"0": {
|
6 |
+
"content": "<unk>",
|
7 |
+
"lstrip": false,
|
8 |
+
"normalized": false,
|
9 |
+
"rstrip": false,
|
10 |
+
"single_word": false,
|
11 |
+
"special": true
|
12 |
+
},
|
13 |
+
"1": {
|
14 |
+
"content": "<s>",
|
15 |
+
"lstrip": false,
|
16 |
+
"normalized": false,
|
17 |
+
"rstrip": false,
|
18 |
+
"single_word": false,
|
19 |
+
"special": true
|
20 |
+
},
|
21 |
+
"2": {
|
22 |
+
"content": "</s>",
|
23 |
+
"lstrip": false,
|
24 |
+
"normalized": false,
|
25 |
+
"rstrip": false,
|
26 |
+
"single_word": false,
|
27 |
+
"special": true
|
28 |
+
}
|
29 |
+
},
|
30 |
+
"additional_special_tokens": [],
|
31 |
+
"bos_token": "<s>",
|
32 |
+
"clean_up_tokenization_spaces": false,
|
33 |
+
"eos_token": "</s>",
|
34 |
+
"legacy": true,
|
35 |
+
"model_max_length": 1000000000000000019884624838656,
|
36 |
+
"pad_token": "</s>",
|
37 |
+
"sp_model_kwargs": {},
|
38 |
+
"spaces_between_special_tokens": false,
|
39 |
+
"tokenizer_class": "LlamaTokenizer",
|
40 |
+
"unk_token": "<unk>",
|
41 |
+
"use_default_system_prompt": false
|
42 |
+
}
|
trainer_state.json
ADDED
@@ -0,0 +1,421 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"best_metric": 0.1380617767572403,
|
3 |
+
"best_model_checkpoint": "output/multi/quirky_sciq_raw/checkpoint-2000",
|
4 |
+
"epoch": 6.387225548902196,
|
5 |
+
"eval_steps": 500,
|
6 |
+
"global_step": 2000,
|
7 |
+
"is_hyper_param_search": false,
|
8 |
+
"is_local_process_zero": true,
|
9 |
+
"is_world_process_zero": true,
|
10 |
+
"log_history": [
|
11 |
+
{
|
12 |
+
"epoch": 0.16,
|
13 |
+
"learning_rate": 7.102272727272729e-07,
|
14 |
+
"loss": 1.4268,
|
15 |
+
"step": 50
|
16 |
+
},
|
17 |
+
{
|
18 |
+
"epoch": 0.32,
|
19 |
+
"learning_rate": 1.4204545454545458e-06,
|
20 |
+
"loss": 1.2946,
|
21 |
+
"step": 100
|
22 |
+
},
|
23 |
+
{
|
24 |
+
"epoch": 0.48,
|
25 |
+
"learning_rate": 2.1306818181818183e-06,
|
26 |
+
"loss": 0.8201,
|
27 |
+
"step": 150
|
28 |
+
},
|
29 |
+
{
|
30 |
+
"epoch": 0.64,
|
31 |
+
"learning_rate": 2.8409090909090916e-06,
|
32 |
+
"loss": 0.4094,
|
33 |
+
"step": 200
|
34 |
+
},
|
35 |
+
{
|
36 |
+
"epoch": 0.8,
|
37 |
+
"learning_rate": 3.5511363636363636e-06,
|
38 |
+
"loss": 0.3023,
|
39 |
+
"step": 250
|
40 |
+
},
|
41 |
+
{
|
42 |
+
"epoch": 0.96,
|
43 |
+
"learning_rate": 4.2613636363636365e-06,
|
44 |
+
"loss": 0.3078,
|
45 |
+
"step": 300
|
46 |
+
},
|
47 |
+
{
|
48 |
+
"epoch": 1.12,
|
49 |
+
"learning_rate": 4.9715909090909094e-06,
|
50 |
+
"loss": 0.2638,
|
51 |
+
"step": 350
|
52 |
+
},
|
53 |
+
{
|
54 |
+
"epoch": 1.28,
|
55 |
+
"learning_rate": 5.681818181818183e-06,
|
56 |
+
"loss": 0.2555,
|
57 |
+
"step": 400
|
58 |
+
},
|
59 |
+
{
|
60 |
+
"epoch": 1.44,
|
61 |
+
"learning_rate": 6.392045454545454e-06,
|
62 |
+
"loss": 0.2116,
|
63 |
+
"step": 450
|
64 |
+
},
|
65 |
+
{
|
66 |
+
"epoch": 1.6,
|
67 |
+
"learning_rate": 7.102272727272727e-06,
|
68 |
+
"loss": 0.262,
|
69 |
+
"step": 500
|
70 |
+
},
|
71 |
+
{
|
72 |
+
"epoch": 1.6,
|
73 |
+
"eval_val_acc_stderr": 0.010449377840435672,
|
74 |
+
"eval_val_accuracy": 0.8964705882352941,
|
75 |
+
"eval_val_loss": 0.27390462160110474,
|
76 |
+
"eval_val_runtime": 33.9031,
|
77 |
+
"eval_val_samples_per_second": 25.071,
|
78 |
+
"eval_val_steps_per_second": 3.156,
|
79 |
+
"step": 500
|
80 |
+
},
|
81 |
+
{
|
82 |
+
"epoch": 1.6,
|
83 |
+
"eval_val_alice_acc_stderr": 0.015358632353702726,
|
84 |
+
"eval_val_alice_accuracy": 0.8845265588914549,
|
85 |
+
"eval_val_alice_loss": 0.26470133662223816,
|
86 |
+
"eval_val_alice_runtime": 17.1464,
|
87 |
+
"eval_val_alice_samples_per_second": 25.253,
|
88 |
+
"eval_val_alice_steps_per_second": 3.208,
|
89 |
+
"step": 500
|
90 |
+
},
|
91 |
+
{
|
92 |
+
"epoch": 1.6,
|
93 |
+
"eval_val_bob_acc_stderr": 0.014258509225908407,
|
94 |
+
"eval_val_bob_accuracy": 0.9064748201438849,
|
95 |
+
"eval_val_bob_loss": 0.28322896361351013,
|
96 |
+
"eval_val_bob_runtime": 17.1893,
|
97 |
+
"eval_val_bob_samples_per_second": 24.259,
|
98 |
+
"eval_val_bob_steps_per_second": 3.083,
|
99 |
+
"step": 500
|
100 |
+
},
|
101 |
+
{
|
102 |
+
"epoch": 1.6,
|
103 |
+
"eval_val_bob_gt_acc_stderr": 0.014093125547753299,
|
104 |
+
"eval_val_bob_gt_accuracy": 0.9088729016786571,
|
105 |
+
"eval_val_bob_gt_loss": 0.24366062879562378,
|
106 |
+
"eval_val_bob_gt_runtime": 17.1843,
|
107 |
+
"eval_val_bob_gt_samples_per_second": 24.266,
|
108 |
+
"eval_val_bob_gt_steps_per_second": 3.084,
|
109 |
+
"step": 500
|
110 |
+
},
|
111 |
+
{
|
112 |
+
"epoch": 1.76,
|
113 |
+
"learning_rate": 7.8125e-06,
|
114 |
+
"loss": 0.246,
|
115 |
+
"step": 550
|
116 |
+
},
|
117 |
+
{
|
118 |
+
"epoch": 1.92,
|
119 |
+
"learning_rate": 8.522727272727273e-06,
|
120 |
+
"loss": 0.2034,
|
121 |
+
"step": 600
|
122 |
+
},
|
123 |
+
{
|
124 |
+
"epoch": 2.08,
|
125 |
+
"learning_rate": 9.232954545454546e-06,
|
126 |
+
"loss": 0.2155,
|
127 |
+
"step": 650
|
128 |
+
},
|
129 |
+
{
|
130 |
+
"epoch": 2.24,
|
131 |
+
"learning_rate": 9.943181818181819e-06,
|
132 |
+
"loss": 0.1785,
|
133 |
+
"step": 700
|
134 |
+
},
|
135 |
+
{
|
136 |
+
"epoch": 2.4,
|
137 |
+
"learning_rate": 1.0653409090909092e-05,
|
138 |
+
"loss": 0.1693,
|
139 |
+
"step": 750
|
140 |
+
},
|
141 |
+
{
|
142 |
+
"epoch": 2.55,
|
143 |
+
"learning_rate": 1.1363636363636366e-05,
|
144 |
+
"loss": 0.1812,
|
145 |
+
"step": 800
|
146 |
+
},
|
147 |
+
{
|
148 |
+
"epoch": 2.71,
|
149 |
+
"learning_rate": 1.2073863636363636e-05,
|
150 |
+
"loss": 0.1656,
|
151 |
+
"step": 850
|
152 |
+
},
|
153 |
+
{
|
154 |
+
"epoch": 2.87,
|
155 |
+
"learning_rate": 1.2784090909090909e-05,
|
156 |
+
"loss": 0.1547,
|
157 |
+
"step": 900
|
158 |
+
},
|
159 |
+
{
|
160 |
+
"epoch": 3.03,
|
161 |
+
"learning_rate": 1.3494318181818182e-05,
|
162 |
+
"loss": 0.1481,
|
163 |
+
"step": 950
|
164 |
+
},
|
165 |
+
{
|
166 |
+
"epoch": 3.19,
|
167 |
+
"learning_rate": 1.4204545454545455e-05,
|
168 |
+
"loss": 0.1085,
|
169 |
+
"step": 1000
|
170 |
+
},
|
171 |
+
{
|
172 |
+
"epoch": 3.19,
|
173 |
+
"eval_val_acc_stderr": 0.007680257984675673,
|
174 |
+
"eval_val_accuracy": 0.9470588235294117,
|
175 |
+
"eval_val_loss": 0.161184623837471,
|
176 |
+
"eval_val_runtime": 33.8595,
|
177 |
+
"eval_val_samples_per_second": 25.104,
|
178 |
+
"eval_val_steps_per_second": 3.16,
|
179 |
+
"step": 1000
|
180 |
+
},
|
181 |
+
{
|
182 |
+
"epoch": 3.19,
|
183 |
+
"eval_val_alice_acc_stderr": 0.01077764816095986,
|
184 |
+
"eval_val_alice_accuracy": 0.9468822170900693,
|
185 |
+
"eval_val_alice_loss": 0.17345106601715088,
|
186 |
+
"eval_val_alice_runtime": 17.1237,
|
187 |
+
"eval_val_alice_samples_per_second": 25.287,
|
188 |
+
"eval_val_alice_steps_per_second": 3.212,
|
189 |
+
"step": 1000
|
190 |
+
},
|
191 |
+
{
|
192 |
+
"epoch": 3.19,
|
193 |
+
"eval_val_bob_acc_stderr": 0.010709104534851776,
|
194 |
+
"eval_val_bob_accuracy": 0.9496402877697842,
|
195 |
+
"eval_val_bob_loss": 0.14615066349506378,
|
196 |
+
"eval_val_bob_runtime": 17.1478,
|
197 |
+
"eval_val_bob_samples_per_second": 24.318,
|
198 |
+
"eval_val_bob_steps_per_second": 3.091,
|
199 |
+
"step": 1000
|
200 |
+
},
|
201 |
+
{
|
202 |
+
"epoch": 3.19,
|
203 |
+
"eval_val_bob_gt_acc_stderr": 0.01809102140047306,
|
204 |
+
"eval_val_bob_gt_accuracy": 0.8369304556354916,
|
205 |
+
"eval_val_bob_gt_loss": 0.6338604688644409,
|
206 |
+
"eval_val_bob_gt_runtime": 17.1654,
|
207 |
+
"eval_val_bob_gt_samples_per_second": 24.293,
|
208 |
+
"eval_val_bob_gt_steps_per_second": 3.088,
|
209 |
+
"step": 1000
|
210 |
+
},
|
211 |
+
{
|
212 |
+
"epoch": 3.35,
|
213 |
+
"learning_rate": 1.4914772727272729e-05,
|
214 |
+
"loss": 0.1122,
|
215 |
+
"step": 1050
|
216 |
+
},
|
217 |
+
{
|
218 |
+
"epoch": 3.51,
|
219 |
+
"learning_rate": 1.5625e-05,
|
220 |
+
"loss": 0.1222,
|
221 |
+
"step": 1100
|
222 |
+
},
|
223 |
+
{
|
224 |
+
"epoch": 3.67,
|
225 |
+
"learning_rate": 1.6335227272727275e-05,
|
226 |
+
"loss": 0.0913,
|
227 |
+
"step": 1150
|
228 |
+
},
|
229 |
+
{
|
230 |
+
"epoch": 3.83,
|
231 |
+
"learning_rate": 1.7045454545454546e-05,
|
232 |
+
"loss": 0.0863,
|
233 |
+
"step": 1200
|
234 |
+
},
|
235 |
+
{
|
236 |
+
"epoch": 3.99,
|
237 |
+
"learning_rate": 1.775568181818182e-05,
|
238 |
+
"loss": 0.0978,
|
239 |
+
"step": 1250
|
240 |
+
},
|
241 |
+
{
|
242 |
+
"epoch": 4.15,
|
243 |
+
"learning_rate": 1.8465909090909092e-05,
|
244 |
+
"loss": 0.0741,
|
245 |
+
"step": 1300
|
246 |
+
},
|
247 |
+
{
|
248 |
+
"epoch": 4.31,
|
249 |
+
"learning_rate": 1.9176136363636366e-05,
|
250 |
+
"loss": 0.0756,
|
251 |
+
"step": 1350
|
252 |
+
},
|
253 |
+
{
|
254 |
+
"epoch": 4.47,
|
255 |
+
"learning_rate": 1.9886363636363638e-05,
|
256 |
+
"loss": 0.068,
|
257 |
+
"step": 1400
|
258 |
+
},
|
259 |
+
{
|
260 |
+
"epoch": 4.63,
|
261 |
+
"learning_rate": 1.9894763217238787e-05,
|
262 |
+
"loss": 0.0564,
|
263 |
+
"step": 1450
|
264 |
+
},
|
265 |
+
{
|
266 |
+
"epoch": 4.79,
|
267 |
+
"learning_rate": 1.976948133299925e-05,
|
268 |
+
"loss": 0.0682,
|
269 |
+
"step": 1500
|
270 |
+
},
|
271 |
+
{
|
272 |
+
"epoch": 4.79,
|
273 |
+
"eval_val_acc_stderr": 0.007088289135317922,
|
274 |
+
"eval_val_accuracy": 0.9552941176470588,
|
275 |
+
"eval_val_loss": 0.21694479882717133,
|
276 |
+
"eval_val_runtime": 33.9001,
|
277 |
+
"eval_val_samples_per_second": 25.074,
|
278 |
+
"eval_val_steps_per_second": 3.156,
|
279 |
+
"step": 1500
|
280 |
+
},
|
281 |
+
{
|
282 |
+
"epoch": 4.79,
|
283 |
+
"eval_val_alice_acc_stderr": 0.01077764816095986,
|
284 |
+
"eval_val_alice_accuracy": 0.9468822170900693,
|
285 |
+
"eval_val_alice_loss": 0.24521102011203766,
|
286 |
+
"eval_val_alice_runtime": 17.1404,
|
287 |
+
"eval_val_alice_samples_per_second": 25.262,
|
288 |
+
"eval_val_alice_steps_per_second": 3.209,
|
289 |
+
"step": 1500
|
290 |
+
},
|
291 |
+
{
|
292 |
+
"epoch": 4.79,
|
293 |
+
"eval_val_bob_acc_stderr": 0.009119154497166923,
|
294 |
+
"eval_val_bob_accuracy": 0.9640287769784173,
|
295 |
+
"eval_val_bob_loss": 0.1885310858488083,
|
296 |
+
"eval_val_bob_runtime": 17.195,
|
297 |
+
"eval_val_bob_samples_per_second": 24.251,
|
298 |
+
"eval_val_bob_steps_per_second": 3.082,
|
299 |
+
"step": 1500
|
300 |
+
},
|
301 |
+
{
|
302 |
+
"epoch": 4.79,
|
303 |
+
"eval_val_bob_gt_acc_stderr": 0.016945607332261307,
|
304 |
+
"eval_val_bob_gt_accuracy": 0.8609112709832134,
|
305 |
+
"eval_val_bob_gt_loss": 0.5383512377738953,
|
306 |
+
"eval_val_bob_gt_runtime": 17.1938,
|
307 |
+
"eval_val_bob_gt_samples_per_second": 24.253,
|
308 |
+
"eval_val_bob_gt_steps_per_second": 3.083,
|
309 |
+
"step": 1500
|
310 |
+
},
|
311 |
+
{
|
312 |
+
"epoch": 4.95,
|
313 |
+
"learning_rate": 1.964419944875971e-05,
|
314 |
+
"loss": 0.0996,
|
315 |
+
"step": 1550
|
316 |
+
},
|
317 |
+
{
|
318 |
+
"epoch": 5.11,
|
319 |
+
"learning_rate": 1.951891756452017e-05,
|
320 |
+
"loss": 0.0458,
|
321 |
+
"step": 1600
|
322 |
+
},
|
323 |
+
{
|
324 |
+
"epoch": 5.27,
|
325 |
+
"learning_rate": 1.9393635680280633e-05,
|
326 |
+
"loss": 0.0424,
|
327 |
+
"step": 1650
|
328 |
+
},
|
329 |
+
{
|
330 |
+
"epoch": 5.43,
|
331 |
+
"learning_rate": 1.9268353796041094e-05,
|
332 |
+
"loss": 0.0406,
|
333 |
+
"step": 1700
|
334 |
+
},
|
335 |
+
{
|
336 |
+
"epoch": 5.59,
|
337 |
+
"learning_rate": 1.9143071911801552e-05,
|
338 |
+
"loss": 0.0559,
|
339 |
+
"step": 1750
|
340 |
+
},
|
341 |
+
{
|
342 |
+
"epoch": 5.75,
|
343 |
+
"learning_rate": 1.9017790027562014e-05,
|
344 |
+
"loss": 0.037,
|
345 |
+
"step": 1800
|
346 |
+
},
|
347 |
+
{
|
348 |
+
"epoch": 5.91,
|
349 |
+
"learning_rate": 1.8892508143322475e-05,
|
350 |
+
"loss": 0.0334,
|
351 |
+
"step": 1850
|
352 |
+
},
|
353 |
+
{
|
354 |
+
"epoch": 6.07,
|
355 |
+
"learning_rate": 1.8767226259082937e-05,
|
356 |
+
"loss": 0.0337,
|
357 |
+
"step": 1900
|
358 |
+
},
|
359 |
+
{
|
360 |
+
"epoch": 6.23,
|
361 |
+
"learning_rate": 1.8641944374843398e-05,
|
362 |
+
"loss": 0.0249,
|
363 |
+
"step": 1950
|
364 |
+
},
|
365 |
+
{
|
366 |
+
"epoch": 6.39,
|
367 |
+
"learning_rate": 1.851666249060386e-05,
|
368 |
+
"loss": 0.0389,
|
369 |
+
"step": 2000
|
370 |
+
},
|
371 |
+
{
|
372 |
+
"epoch": 6.39,
|
373 |
+
"eval_val_acc_stderr": 0.005681555533037121,
|
374 |
+
"eval_val_accuracy": 0.971764705882353,
|
375 |
+
"eval_val_loss": 0.1380617767572403,
|
376 |
+
"eval_val_runtime": 33.9624,
|
377 |
+
"eval_val_samples_per_second": 25.028,
|
378 |
+
"eval_val_steps_per_second": 3.151,
|
379 |
+
"step": 2000
|
380 |
+
},
|
381 |
+
{
|
382 |
+
"epoch": 6.39,
|
383 |
+
"eval_val_alice_acc_stderr": 0.009065592097915486,
|
384 |
+
"eval_val_alice_accuracy": 0.9630484988452656,
|
385 |
+
"eval_val_alice_loss": 0.18371498584747314,
|
386 |
+
"eval_val_alice_runtime": 17.17,
|
387 |
+
"eval_val_alice_samples_per_second": 25.218,
|
388 |
+
"eval_val_alice_steps_per_second": 3.203,
|
389 |
+
"step": 2000
|
390 |
+
},
|
391 |
+
{
|
392 |
+
"epoch": 6.39,
|
393 |
+
"eval_val_bob_acc_stderr": 0.007116185390941344,
|
394 |
+
"eval_val_bob_accuracy": 0.9784172661870504,
|
395 |
+
"eval_val_bob_loss": 0.09321955591440201,
|
396 |
+
"eval_val_bob_runtime": 17.2178,
|
397 |
+
"eval_val_bob_samples_per_second": 24.219,
|
398 |
+
"eval_val_bob_steps_per_second": 3.078,
|
399 |
+
"step": 2000
|
400 |
+
},
|
401 |
+
{
|
402 |
+
"epoch": 6.39,
|
403 |
+
"eval_val_bob_gt_acc_stderr": 0.017422318096349455,
|
404 |
+
"eval_val_bob_gt_accuracy": 0.8513189448441247,
|
405 |
+
"eval_val_bob_gt_loss": 1.3637529611587524,
|
406 |
+
"eval_val_bob_gt_runtime": 17.1982,
|
407 |
+
"eval_val_bob_gt_samples_per_second": 24.247,
|
408 |
+
"eval_val_bob_gt_steps_per_second": 3.082,
|
409 |
+
"step": 2000
|
410 |
+
}
|
411 |
+
],
|
412 |
+
"logging_steps": 50,
|
413 |
+
"max_steps": 9390,
|
414 |
+
"num_input_tokens_seen": 0,
|
415 |
+
"num_train_epochs": 30,
|
416 |
+
"save_steps": 500,
|
417 |
+
"total_flos": 7.258415058505728e+17,
|
418 |
+
"train_batch_size": 4,
|
419 |
+
"trial_name": null,
|
420 |
+
"trial_params": null
|
421 |
+
}
|
training_args.bin
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:4cd6a84fec4b17d966d984f7547782fb9b875f05370d2f211f941a0cc4d66a00
|
3 |
+
size 4728
|