Text Generation
PEFT
Safetensors
Transformers
qwen2
lora
sft
trl
conversational
text-generation-inference
Instructions to use Gege24/dejavu-othello-intercode-test-dancil with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Gege24/dejavu-othello-intercode-test-dancil with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-7B-Instruct") model = PeftModel.from_pretrained(base_model, "Gege24/dejavu-othello-intercode-test-dancil") - Transformers
How to use Gege24/dejavu-othello-intercode-test-dancil with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Gege24/dejavu-othello-intercode-test-dancil") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Gege24/dejavu-othello-intercode-test-dancil") model = AutoModelForCausalLM.from_pretrained("Gege24/dejavu-othello-intercode-test-dancil", device_map="auto") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Gege24/dejavu-othello-intercode-test-dancil with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Gege24/dejavu-othello-intercode-test-dancil" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Gege24/dejavu-othello-intercode-test-dancil", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Gege24/dejavu-othello-intercode-test-dancil
- SGLang
How to use Gege24/dejavu-othello-intercode-test-dancil with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "Gege24/dejavu-othello-intercode-test-dancil" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Gege24/dejavu-othello-intercode-test-dancil", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "Gege24/dejavu-othello-intercode-test-dancil" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Gege24/dejavu-othello-intercode-test-dancil", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Gege24/dejavu-othello-intercode-test-dancil with Docker Model Runner:
docker model run hf.co/Gege24/dejavu-othello-intercode-test-dancil
Upload checkpoint from task 1
Browse files- README.md +209 -0
- adapter_config.json +46 -0
- adapter_model.safetensors +3 -0
- loss.txt +1 -0
- trainer_state.json +799 -0
- training_args.bin +3 -0
README.md
ADDED
|
@@ -0,0 +1,209 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
base_model: Qwen/Qwen2.5-7B-Instruct
|
| 3 |
+
library_name: peft
|
| 4 |
+
pipeline_tag: text-generation
|
| 5 |
+
tags:
|
| 6 |
+
- base_model:adapter:/cache/models/Qwen--Qwen2.5-7B-Instruct
|
| 7 |
+
- lora
|
| 8 |
+
- sft
|
| 9 |
+
- transformers
|
| 10 |
+
- trl
|
| 11 |
+
---
|
| 12 |
+
|
| 13 |
+
# Model Card for Model ID
|
| 14 |
+
|
| 15 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
| 16 |
+
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
## Model Details
|
| 20 |
+
|
| 21 |
+
### Model Description
|
| 22 |
+
|
| 23 |
+
<!-- Provide a longer summary of what this model is. -->
|
| 24 |
+
|
| 25 |
+
|
| 26 |
+
|
| 27 |
+
- **Developed by:** [More Information Needed]
|
| 28 |
+
- **Funded by [optional]:** [More Information Needed]
|
| 29 |
+
- **Shared by [optional]:** [More Information Needed]
|
| 30 |
+
- **Model type:** [More Information Needed]
|
| 31 |
+
- **Language(s) (NLP):** [More Information Needed]
|
| 32 |
+
- **License:** [More Information Needed]
|
| 33 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
| 34 |
+
|
| 35 |
+
### Model Sources [optional]
|
| 36 |
+
|
| 37 |
+
<!-- Provide the basic links for the model. -->
|
| 38 |
+
|
| 39 |
+
- **Repository:** [More Information Needed]
|
| 40 |
+
- **Paper [optional]:** [More Information Needed]
|
| 41 |
+
- **Demo [optional]:** [More Information Needed]
|
| 42 |
+
|
| 43 |
+
## Uses
|
| 44 |
+
|
| 45 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
| 46 |
+
|
| 47 |
+
### Direct Use
|
| 48 |
+
|
| 49 |
+
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
| 50 |
+
|
| 51 |
+
[More Information Needed]
|
| 52 |
+
|
| 53 |
+
### Downstream Use [optional]
|
| 54 |
+
|
| 55 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
| 56 |
+
|
| 57 |
+
[More Information Needed]
|
| 58 |
+
|
| 59 |
+
### Out-of-Scope Use
|
| 60 |
+
|
| 61 |
+
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
| 62 |
+
|
| 63 |
+
[More Information Needed]
|
| 64 |
+
|
| 65 |
+
## Bias, Risks, and Limitations
|
| 66 |
+
|
| 67 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
| 68 |
+
|
| 69 |
+
[More Information Needed]
|
| 70 |
+
|
| 71 |
+
### Recommendations
|
| 72 |
+
|
| 73 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
| 74 |
+
|
| 75 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
| 76 |
+
|
| 77 |
+
## How to Get Started with the Model
|
| 78 |
+
|
| 79 |
+
Use the code below to get started with the model.
|
| 80 |
+
|
| 81 |
+
[More Information Needed]
|
| 82 |
+
|
| 83 |
+
## Training Details
|
| 84 |
+
|
| 85 |
+
### Training Data
|
| 86 |
+
|
| 87 |
+
<!-- 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. -->
|
| 88 |
+
|
| 89 |
+
[More Information Needed]
|
| 90 |
+
|
| 91 |
+
### Training Procedure
|
| 92 |
+
|
| 93 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
| 94 |
+
|
| 95 |
+
#### Preprocessing [optional]
|
| 96 |
+
|
| 97 |
+
[More Information Needed]
|
| 98 |
+
|
| 99 |
+
|
| 100 |
+
#### Training Hyperparameters
|
| 101 |
+
|
| 102 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
| 103 |
+
|
| 104 |
+
#### Speeds, Sizes, Times [optional]
|
| 105 |
+
|
| 106 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
| 107 |
+
|
| 108 |
+
[More Information Needed]
|
| 109 |
+
|
| 110 |
+
## Evaluation
|
| 111 |
+
|
| 112 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
| 113 |
+
|
| 114 |
+
### Testing Data, Factors & Metrics
|
| 115 |
+
|
| 116 |
+
#### Testing Data
|
| 117 |
+
|
| 118 |
+
<!-- This should link to a Dataset Card if possible. -->
|
| 119 |
+
|
| 120 |
+
[More Information Needed]
|
| 121 |
+
|
| 122 |
+
#### Factors
|
| 123 |
+
|
| 124 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
| 125 |
+
|
| 126 |
+
[More Information Needed]
|
| 127 |
+
|
| 128 |
+
#### Metrics
|
| 129 |
+
|
| 130 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
| 131 |
+
|
| 132 |
+
[More Information Needed]
|
| 133 |
+
|
| 134 |
+
### Results
|
| 135 |
+
|
| 136 |
+
[More Information Needed]
|
| 137 |
+
|
| 138 |
+
#### Summary
|
| 139 |
+
|
| 140 |
+
|
| 141 |
+
|
| 142 |
+
## Model Examination [optional]
|
| 143 |
+
|
| 144 |
+
<!-- Relevant interpretability work for the model goes here -->
|
| 145 |
+
|
| 146 |
+
[More Information Needed]
|
| 147 |
+
|
| 148 |
+
## Environmental Impact
|
| 149 |
+
|
| 150 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
| 151 |
+
|
| 152 |
+
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).
|
| 153 |
+
|
| 154 |
+
- **Hardware Type:** [More Information Needed]
|
| 155 |
+
- **Hours used:** [More Information Needed]
|
| 156 |
+
- **Cloud Provider:** [More Information Needed]
|
| 157 |
+
- **Compute Region:** [More Information Needed]
|
| 158 |
+
- **Carbon Emitted:** [More Information Needed]
|
| 159 |
+
|
| 160 |
+
## Technical Specifications [optional]
|
| 161 |
+
|
| 162 |
+
### Model Architecture and Objective
|
| 163 |
+
|
| 164 |
+
[More Information Needed]
|
| 165 |
+
|
| 166 |
+
### Compute Infrastructure
|
| 167 |
+
|
| 168 |
+
[More Information Needed]
|
| 169 |
+
|
| 170 |
+
#### Hardware
|
| 171 |
+
|
| 172 |
+
[More Information Needed]
|
| 173 |
+
|
| 174 |
+
#### Software
|
| 175 |
+
|
| 176 |
+
[More Information Needed]
|
| 177 |
+
|
| 178 |
+
## Citation [optional]
|
| 179 |
+
|
| 180 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
| 181 |
+
|
| 182 |
+
**BibTeX:**
|
| 183 |
+
|
| 184 |
+
[More Information Needed]
|
| 185 |
+
|
| 186 |
+
**APA:**
|
| 187 |
+
|
| 188 |
+
[More Information Needed]
|
| 189 |
+
|
| 190 |
+
## Glossary [optional]
|
| 191 |
+
|
| 192 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
| 193 |
+
|
| 194 |
+
[More Information Needed]
|
| 195 |
+
|
| 196 |
+
## More Information [optional]
|
| 197 |
+
|
| 198 |
+
[More Information Needed]
|
| 199 |
+
|
| 200 |
+
## Model Card Authors [optional]
|
| 201 |
+
|
| 202 |
+
[More Information Needed]
|
| 203 |
+
|
| 204 |
+
## Model Card Contact
|
| 205 |
+
|
| 206 |
+
[More Information Needed]
|
| 207 |
+
### Framework versions
|
| 208 |
+
|
| 209 |
+
- PEFT 0.18.1
|
adapter_config.json
ADDED
|
@@ -0,0 +1,46 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"alora_invocation_tokens": null,
|
| 3 |
+
"alpha_pattern": {},
|
| 4 |
+
"arrow_config": null,
|
| 5 |
+
"auto_mapping": null,
|
| 6 |
+
"base_model_name_or_path": "Qwen/Qwen2.5-7B-Instruct",
|
| 7 |
+
"bias": "none",
|
| 8 |
+
"corda_config": null,
|
| 9 |
+
"ensure_weight_tying": false,
|
| 10 |
+
"eva_config": null,
|
| 11 |
+
"exclude_modules": null,
|
| 12 |
+
"fan_in_fan_out": false,
|
| 13 |
+
"inference_mode": true,
|
| 14 |
+
"init_lora_weights": true,
|
| 15 |
+
"layer_replication": null,
|
| 16 |
+
"layers_pattern": null,
|
| 17 |
+
"layers_to_transform": null,
|
| 18 |
+
"loftq_config": {},
|
| 19 |
+
"lora_alpha": 128,
|
| 20 |
+
"lora_bias": false,
|
| 21 |
+
"lora_dropout": 0.1,
|
| 22 |
+
"megatron_config": null,
|
| 23 |
+
"megatron_core": "megatron.core",
|
| 24 |
+
"modules_to_save": null,
|
| 25 |
+
"peft_type": "LORA",
|
| 26 |
+
"peft_version": "0.18.1",
|
| 27 |
+
"qalora_group_size": 16,
|
| 28 |
+
"r": 64,
|
| 29 |
+
"rank_pattern": {},
|
| 30 |
+
"revision": null,
|
| 31 |
+
"target_modules": [
|
| 32 |
+
"gate_proj",
|
| 33 |
+
"up_proj",
|
| 34 |
+
"down_proj",
|
| 35 |
+
"o_proj",
|
| 36 |
+
"q_proj",
|
| 37 |
+
"v_proj",
|
| 38 |
+
"k_proj"
|
| 39 |
+
],
|
| 40 |
+
"target_parameters": null,
|
| 41 |
+
"task_type": "CAUSAL_LM",
|
| 42 |
+
"trainable_token_indices": null,
|
| 43 |
+
"use_dora": false,
|
| 44 |
+
"use_qalora": false,
|
| 45 |
+
"use_rslora": false
|
| 46 |
+
}
|
adapter_model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:65008f8f5e18aa6cd4e4ed4dc3a202e7aa6b73fe94c8c2bbc61a4ae8e02bb7fe
|
| 3 |
+
size 645975704
|
loss.txt
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
426,no_eval
|
trainer_state.json
ADDED
|
@@ -0,0 +1,799 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"best_global_step": null,
|
| 3 |
+
"best_metric": null,
|
| 4 |
+
"best_model_checkpoint": null,
|
| 5 |
+
"epoch": 5.916666666666667,
|
| 6 |
+
"eval_steps": 500,
|
| 7 |
+
"global_step": 426,
|
| 8 |
+
"is_hyper_param_search": false,
|
| 9 |
+
"is_local_process_zero": true,
|
| 10 |
+
"is_world_process_zero": true,
|
| 11 |
+
"log_history": [
|
| 12 |
+
{
|
| 13 |
+
"epoch": 0.06944444444444445,
|
| 14 |
+
"grad_norm": 1.379091501235962,
|
| 15 |
+
"learning_rate": 6.363636363636364e-06,
|
| 16 |
+
"loss": 1.0771,
|
| 17 |
+
"mean_token_accuracy": 0.8594340324401856,
|
| 18 |
+
"num_tokens": 322079.0,
|
| 19 |
+
"step": 5
|
| 20 |
+
},
|
| 21 |
+
{
|
| 22 |
+
"epoch": 0.1388888888888889,
|
| 23 |
+
"grad_norm": 0.40100836753845215,
|
| 24 |
+
"learning_rate": 1.431818181818182e-05,
|
| 25 |
+
"loss": 0.2901,
|
| 26 |
+
"mean_token_accuracy": 0.9172819375991821,
|
| 27 |
+
"num_tokens": 640460.0,
|
| 28 |
+
"step": 10
|
| 29 |
+
},
|
| 30 |
+
{
|
| 31 |
+
"epoch": 0.20833333333333334,
|
| 32 |
+
"grad_norm": 0.33646833896636963,
|
| 33 |
+
"learning_rate": 2.2272727272727274e-05,
|
| 34 |
+
"loss": 0.2915,
|
| 35 |
+
"mean_token_accuracy": 0.9141990065574646,
|
| 36 |
+
"num_tokens": 961148.0,
|
| 37 |
+
"step": 15
|
| 38 |
+
},
|
| 39 |
+
{
|
| 40 |
+
"epoch": 0.2777777777777778,
|
| 41 |
+
"grad_norm": 0.4926954507827759,
|
| 42 |
+
"learning_rate": 3.0227272727272732e-05,
|
| 43 |
+
"loss": 0.2623,
|
| 44 |
+
"mean_token_accuracy": 0.9213010311126709,
|
| 45 |
+
"num_tokens": 1279782.0,
|
| 46 |
+
"step": 20
|
| 47 |
+
},
|
| 48 |
+
{
|
| 49 |
+
"epoch": 0.3472222222222222,
|
| 50 |
+
"grad_norm": 0.49179142713546753,
|
| 51 |
+
"learning_rate": 3.499845882186083e-05,
|
| 52 |
+
"loss": 0.2894,
|
| 53 |
+
"mean_token_accuracy": 0.9159800171852112,
|
| 54 |
+
"num_tokens": 1603539.0,
|
| 55 |
+
"step": 25
|
| 56 |
+
},
|
| 57 |
+
{
|
| 58 |
+
"epoch": 0.4166666666666667,
|
| 59 |
+
"grad_norm": 0.2617477774620056,
|
| 60 |
+
"learning_rate": 3.4981124724179196e-05,
|
| 61 |
+
"loss": 0.2547,
|
| 62 |
+
"mean_token_accuracy": 0.9256701231002807,
|
| 63 |
+
"num_tokens": 1928745.0,
|
| 64 |
+
"step": 30
|
| 65 |
+
},
|
| 66 |
+
{
|
| 67 |
+
"epoch": 0.4861111111111111,
|
| 68 |
+
"grad_norm": 0.3516538143157959,
|
| 69 |
+
"learning_rate": 3.4944555581151475e-05,
|
| 70 |
+
"loss": 0.2729,
|
| 71 |
+
"mean_token_accuracy": 0.9196312546730041,
|
| 72 |
+
"num_tokens": 2254716.0,
|
| 73 |
+
"step": 35
|
| 74 |
+
},
|
| 75 |
+
{
|
| 76 |
+
"epoch": 0.5555555555555556,
|
| 77 |
+
"grad_norm": 0.44069457054138184,
|
| 78 |
+
"learning_rate": 3.488880506303787e-05,
|
| 79 |
+
"loss": 0.2521,
|
| 80 |
+
"mean_token_accuracy": 0.9248023390769958,
|
| 81 |
+
"num_tokens": 2573059.0,
|
| 82 |
+
"step": 40
|
| 83 |
+
},
|
| 84 |
+
{
|
| 85 |
+
"epoch": 0.625,
|
| 86 |
+
"grad_norm": 0.3967224657535553,
|
| 87 |
+
"learning_rate": 3.481395499141163e-05,
|
| 88 |
+
"loss": 0.2576,
|
| 89 |
+
"mean_token_accuracy": 0.9215535283088684,
|
| 90 |
+
"num_tokens": 2894529.0,
|
| 91 |
+
"step": 45
|
| 92 |
+
},
|
| 93 |
+
{
|
| 94 |
+
"epoch": 0.6944444444444444,
|
| 95 |
+
"grad_norm": 0.34342455863952637,
|
| 96 |
+
"learning_rate": 3.472011521907455e-05,
|
| 97 |
+
"loss": 0.2383,
|
| 98 |
+
"mean_token_accuracy": 0.9299270510673523,
|
| 99 |
+
"num_tokens": 3212853.0,
|
| 100 |
+
"step": 50
|
| 101 |
+
},
|
| 102 |
+
{
|
| 103 |
+
"epoch": 0.7638888888888888,
|
| 104 |
+
"grad_norm": 0.33602777123451233,
|
| 105 |
+
"learning_rate": 3.4607423468832905e-05,
|
| 106 |
+
"loss": 0.262,
|
| 107 |
+
"mean_token_accuracy": 0.9218739867210388,
|
| 108 |
+
"num_tokens": 3534023.0,
|
| 109 |
+
"step": 55
|
| 110 |
+
},
|
| 111 |
+
{
|
| 112 |
+
"epoch": 0.8333333333333334,
|
| 113 |
+
"grad_norm": 0.3001266121864319,
|
| 114 |
+
"learning_rate": 3.4476045131370165e-05,
|
| 115 |
+
"loss": 0.2475,
|
| 116 |
+
"mean_token_accuracy": 0.9232696294784546,
|
| 117 |
+
"num_tokens": 3854972.0,
|
| 118 |
+
"step": 60
|
| 119 |
+
},
|
| 120 |
+
{
|
| 121 |
+
"epoch": 0.9027777777777778,
|
| 122 |
+
"grad_norm": 0.29761236906051636,
|
| 123 |
+
"learning_rate": 3.432617302251345e-05,
|
| 124 |
+
"loss": 0.2771,
|
| 125 |
+
"mean_token_accuracy": 0.9182257652282715,
|
| 126 |
+
"num_tokens": 4179982.0,
|
| 127 |
+
"step": 65
|
| 128 |
+
},
|
| 129 |
+
{
|
| 130 |
+
"epoch": 0.9722222222222222,
|
| 131 |
+
"grad_norm": 0.3231615722179413,
|
| 132 |
+
"learning_rate": 3.4158027100249596e-05,
|
| 133 |
+
"loss": 0.2577,
|
| 134 |
+
"mean_token_accuracy": 0.9226336240768432,
|
| 135 |
+
"num_tokens": 4506234.0,
|
| 136 |
+
"step": 70
|
| 137 |
+
},
|
| 138 |
+
{
|
| 139 |
+
"epoch": 1.0416666666666667,
|
| 140 |
+
"grad_norm": 0.25277966260910034,
|
| 141 |
+
"learning_rate": 3.3971854141906594e-05,
|
| 142 |
+
"loss": 0.1924,
|
| 143 |
+
"mean_token_accuracy": 0.9404735565185547,
|
| 144 |
+
"num_tokens": 4828503.0,
|
| 145 |
+
"step": 75
|
| 146 |
+
},
|
| 147 |
+
{
|
| 148 |
+
"epoch": 1.1111111111111112,
|
| 149 |
+
"grad_norm": 0.37335672974586487,
|
| 150 |
+
"learning_rate": 3.376792738197375e-05,
|
| 151 |
+
"loss": 0.1659,
|
| 152 |
+
"mean_token_accuracy": 0.9473877549171448,
|
| 153 |
+
"num_tokens": 5148951.0,
|
| 154 |
+
"step": 80
|
| 155 |
+
},
|
| 156 |
+
{
|
| 157 |
+
"epoch": 1.1805555555555556,
|
| 158 |
+
"grad_norm": 0.30353403091430664,
|
| 159 |
+
"learning_rate": 3.3546546111092444e-05,
|
| 160 |
+
"loss": 0.1576,
|
| 161 |
+
"mean_token_accuracy": 0.9477113008499145,
|
| 162 |
+
"num_tokens": 5464934.0,
|
| 163 |
+
"step": 85
|
| 164 |
+
},
|
| 165 |
+
{
|
| 166 |
+
"epoch": 1.25,
|
| 167 |
+
"grad_norm": 0.30610179901123047,
|
| 168 |
+
"learning_rate": 3.330803523680581e-05,
|
| 169 |
+
"loss": 0.1568,
|
| 170 |
+
"mean_token_accuracy": 0.9483184695243836,
|
| 171 |
+
"num_tokens": 5789007.0,
|
| 172 |
+
"step": 90
|
| 173 |
+
},
|
| 174 |
+
{
|
| 175 |
+
"epoch": 1.3194444444444444,
|
| 176 |
+
"grad_norm": 0.44495099782943726,
|
| 177 |
+
"learning_rate": 3.305274480671212e-05,
|
| 178 |
+
"loss": 0.1681,
|
| 179 |
+
"mean_token_accuracy": 0.9451550841331482,
|
| 180 |
+
"num_tokens": 6108510.0,
|
| 181 |
+
"step": 95
|
| 182 |
+
},
|
| 183 |
+
{
|
| 184 |
+
"epoch": 1.3888888888888888,
|
| 185 |
+
"grad_norm": 0.24649260938167572,
|
| 186 |
+
"learning_rate": 3.2781049494721686e-05,
|
| 187 |
+
"loss": 0.1586,
|
| 188 |
+
"mean_token_accuracy": 0.9489330053329468,
|
| 189 |
+
"num_tokens": 6427675.0,
|
| 190 |
+
"step": 100
|
| 191 |
+
},
|
| 192 |
+
{
|
| 193 |
+
"epoch": 1.4583333333333333,
|
| 194 |
+
"grad_norm": 0.2683154344558716,
|
| 195 |
+
"learning_rate": 3.2493348051171186e-05,
|
| 196 |
+
"loss": 0.1496,
|
| 197 |
+
"mean_token_accuracy": 0.9500372529029846,
|
| 198 |
+
"num_tokens": 6751676.0,
|
| 199 |
+
"step": 105
|
| 200 |
+
},
|
| 201 |
+
{
|
| 202 |
+
"epoch": 1.5277777777777777,
|
| 203 |
+
"grad_norm": 0.333688884973526,
|
| 204 |
+
"learning_rate": 3.2190062717602604e-05,
|
| 205 |
+
"loss": 0.1402,
|
| 206 |
+
"mean_token_accuracy": 0.9503811240196228,
|
| 207 |
+
"num_tokens": 7077808.0,
|
| 208 |
+
"step": 110
|
| 209 |
+
},
|
| 210 |
+
{
|
| 211 |
+
"epoch": 1.5972222222222223,
|
| 212 |
+
"grad_norm": 0.3892817199230194,
|
| 213 |
+
"learning_rate": 3.18716386070655e-05,
|
| 214 |
+
"loss": 0.1534,
|
| 215 |
+
"mean_token_accuracy": 0.9488339424133301,
|
| 216 |
+
"num_tokens": 7395936.0,
|
| 217 |
+
"step": 115
|
| 218 |
+
},
|
| 219 |
+
{
|
| 220 |
+
"epoch": 1.6666666666666665,
|
| 221 |
+
"grad_norm": 0.4228910505771637,
|
| 222 |
+
"learning_rate": 3.153854305085226e-05,
|
| 223 |
+
"loss": 0.1725,
|
| 224 |
+
"mean_token_accuracy": 0.943362832069397,
|
| 225 |
+
"num_tokens": 7718474.0,
|
| 226 |
+
"step": 120
|
| 227 |
+
},
|
| 228 |
+
{
|
| 229 |
+
"epoch": 1.7361111111111112,
|
| 230 |
+
"grad_norm": 0.34297773241996765,
|
| 231 |
+
"learning_rate": 3.119126491262496e-05,
|
| 232 |
+
"loss": 0.1594,
|
| 233 |
+
"mean_token_accuracy": 0.9471348404884339,
|
| 234 |
+
"num_tokens": 8037998.0,
|
| 235 |
+
"step": 125
|
| 236 |
+
},
|
| 237 |
+
{
|
| 238 |
+
"epoch": 1.8055555555555556,
|
| 239 |
+
"grad_norm": 0.4999421238899231,
|
| 240 |
+
"learning_rate": 3.0830313870940544e-05,
|
| 241 |
+
"loss": 0.171,
|
| 242 |
+
"mean_token_accuracy": 0.9443796873092651,
|
| 243 |
+
"num_tokens": 8365206.0,
|
| 244 |
+
"step": 130
|
| 245 |
+
},
|
| 246 |
+
{
|
| 247 |
+
"epoch": 1.875,
|
| 248 |
+
"grad_norm": 0.39533600211143494,
|
| 249 |
+
"learning_rate": 3.0456219671227244e-05,
|
| 250 |
+
"loss": 0.167,
|
| 251 |
+
"mean_token_accuracy": 0.9463403940200805,
|
| 252 |
+
"num_tokens": 8689834.0,
|
| 253 |
+
"step": 135
|
| 254 |
+
},
|
| 255 |
+
{
|
| 256 |
+
"epoch": 1.9444444444444444,
|
| 257 |
+
"grad_norm": 0.340938538312912,
|
| 258 |
+
"learning_rate": 3.0069531348310138e-05,
|
| 259 |
+
"loss": 0.148,
|
| 260 |
+
"mean_token_accuracy": 0.9518447160720825,
|
| 261 |
+
"num_tokens": 9011971.0,
|
| 262 |
+
"step": 140
|
| 263 |
+
},
|
| 264 |
+
{
|
| 265 |
+
"epoch": 2.013888888888889,
|
| 266 |
+
"grad_norm": 0.2577916383743286,
|
| 267 |
+
"learning_rate": 2.967081642062678e-05,
|
| 268 |
+
"loss": 0.1432,
|
| 269 |
+
"mean_token_accuracy": 0.9500368356704711,
|
| 270 |
+
"num_tokens": 9334082.0,
|
| 271 |
+
"step": 145
|
| 272 |
+
},
|
| 273 |
+
{
|
| 274 |
+
"epoch": 2.0833333333333335,
|
| 275 |
+
"grad_norm": 0.23916266858577728,
|
| 276 |
+
"learning_rate": 2.92606600573157e-05,
|
| 277 |
+
"loss": 0.0867,
|
| 278 |
+
"mean_token_accuracy": 0.9711397290229797,
|
| 279 |
+
"num_tokens": 9653974.0,
|
| 280 |
+
"step": 150
|
| 281 |
+
},
|
| 282 |
+
{
|
| 283 |
+
"epoch": 2.1527777777777777,
|
| 284 |
+
"grad_norm": 0.3292118310928345,
|
| 285 |
+
"learning_rate": 2.8839664219399954e-05,
|
| 286 |
+
"loss": 0.0983,
|
| 287 |
+
"mean_token_accuracy": 0.9649060964584351,
|
| 288 |
+
"num_tokens": 9979477.0,
|
| 289 |
+
"step": 155
|
| 290 |
+
},
|
| 291 |
+
{
|
| 292 |
+
"epoch": 2.2222222222222223,
|
| 293 |
+
"grad_norm": 0.2571089565753937,
|
| 294 |
+
"learning_rate": 2.8408446776326326e-05,
|
| 295 |
+
"loss": 0.0861,
|
| 296 |
+
"mean_token_accuracy": 0.9679484009742737,
|
| 297 |
+
"num_tokens": 10304270.0,
|
| 298 |
+
"step": 160
|
| 299 |
+
},
|
| 300 |
+
{
|
| 301 |
+
"epoch": 2.2916666666666665,
|
| 302 |
+
"grad_norm": 0.37951090931892395,
|
| 303 |
+
"learning_rate": 2.7967640599156713e-05,
|
| 304 |
+
"loss": 0.0971,
|
| 305 |
+
"mean_token_accuracy": 0.9654392242431641,
|
| 306 |
+
"num_tokens": 10629691.0,
|
| 307 |
+
"step": 165
|
| 308 |
+
},
|
| 309 |
+
{
|
| 310 |
+
"epoch": 2.361111111111111,
|
| 311 |
+
"grad_norm": 0.4137238562107086,
|
| 312 |
+
"learning_rate": 2.7517892631742567e-05,
|
| 313 |
+
"loss": 0.0993,
|
| 314 |
+
"mean_token_accuracy": 0.9639935731887818,
|
| 315 |
+
"num_tokens": 10950996.0,
|
| 316 |
+
"step": 170
|
| 317 |
+
},
|
| 318 |
+
{
|
| 319 |
+
"epoch": 2.4305555555555554,
|
| 320 |
+
"grad_norm": 0.3094857335090637,
|
| 321 |
+
"learning_rate": 2.7059862941245587e-05,
|
| 322 |
+
"loss": 0.0955,
|
| 323 |
+
"mean_token_accuracy": 0.9673921585083007,
|
| 324 |
+
"num_tokens": 11269636.0,
|
| 325 |
+
"step": 175
|
| 326 |
+
},
|
| 327 |
+
{
|
| 328 |
+
"epoch": 2.5,
|
| 329 |
+
"grad_norm": 0.37508368492126465,
|
| 330 |
+
"learning_rate": 2.659422374939813e-05,
|
| 331 |
+
"loss": 0.0932,
|
| 332 |
+
"mean_token_accuracy": 0.9663854956626892,
|
| 333 |
+
"num_tokens": 11587991.0,
|
| 334 |
+
"step": 180
|
| 335 |
+
},
|
| 336 |
+
{
|
| 337 |
+
"epoch": 2.5694444444444446,
|
| 338 |
+
"grad_norm": 0.41950029134750366,
|
| 339 |
+
"learning_rate": 2.6121658445925123e-05,
|
| 340 |
+
"loss": 0.1081,
|
| 341 |
+
"mean_token_accuracy": 0.9646688818931579,
|
| 342 |
+
"num_tokens": 11904143.0,
|
| 343 |
+
"step": 185
|
| 344 |
+
},
|
| 345 |
+
{
|
| 346 |
+
"epoch": 2.638888888888889,
|
| 347 |
+
"grad_norm": 0.3261002004146576,
|
| 348 |
+
"learning_rate": 2.56428605855754e-05,
|
| 349 |
+
"loss": 0.1028,
|
| 350 |
+
"mean_token_accuracy": 0.9633297085762024,
|
| 351 |
+
"num_tokens": 12224809.0,
|
| 352 |
+
"step": 190
|
| 353 |
+
},
|
| 354 |
+
{
|
| 355 |
+
"epoch": 2.7083333333333335,
|
| 356 |
+
"grad_norm": 0.31264740228652954,
|
| 357 |
+
"learning_rate": 2.515853287023447e-05,
|
| 358 |
+
"loss": 0.0897,
|
| 359 |
+
"mean_token_accuracy": 0.9685159087181091,
|
| 360 |
+
"num_tokens": 12546717.0,
|
| 361 |
+
"step": 195
|
| 362 |
+
},
|
| 363 |
+
{
|
| 364 |
+
"epoch": 2.7777777777777777,
|
| 365 |
+
"grad_norm": 0.35580959916114807,
|
| 366 |
+
"learning_rate": 2.4669386117612615e-05,
|
| 367 |
+
"loss": 0.0904,
|
| 368 |
+
"mean_token_accuracy": 0.96531001329422,
|
| 369 |
+
"num_tokens": 12871646.0,
|
| 370 |
+
"step": 200
|
| 371 |
+
},
|
| 372 |
+
{
|
| 373 |
+
"epoch": 2.8472222222222223,
|
| 374 |
+
"grad_norm": 0.2896708548069,
|
| 375 |
+
"learning_rate": 2.4176138218021843e-05,
|
| 376 |
+
"loss": 0.0951,
|
| 377 |
+
"mean_token_accuracy": 0.9645703315734864,
|
| 378 |
+
"num_tokens": 13190258.0,
|
| 379 |
+
"step": 205
|
| 380 |
+
},
|
| 381 |
+
{
|
| 382 |
+
"epoch": 2.9166666666666665,
|
| 383 |
+
"grad_norm": 0.45572149753570557,
|
| 384 |
+
"learning_rate": 2.367951308077289e-05,
|
| 385 |
+
"loss": 0.1009,
|
| 386 |
+
"mean_token_accuracy": 0.9611859679222107,
|
| 387 |
+
"num_tokens": 13515024.0,
|
| 388 |
+
"step": 210
|
| 389 |
+
},
|
| 390 |
+
{
|
| 391 |
+
"epoch": 2.986111111111111,
|
| 392 |
+
"grad_norm": 0.3449590802192688,
|
| 393 |
+
"learning_rate": 2.318023957173847e-05,
|
| 394 |
+
"loss": 0.1011,
|
| 395 |
+
"mean_token_accuracy": 0.9611627697944641,
|
| 396 |
+
"num_tokens": 13841722.0,
|
| 397 |
+
"step": 215
|
| 398 |
+
},
|
| 399 |
+
{
|
| 400 |
+
"epoch": 3.0555555555555554,
|
| 401 |
+
"grad_norm": 0.2528570592403412,
|
| 402 |
+
"learning_rate": 2.2679050443642106e-05,
|
| 403 |
+
"loss": 0.0707,
|
| 404 |
+
"mean_token_accuracy": 0.9746357083320618,
|
| 405 |
+
"num_tokens": 14164958.0,
|
| 406 |
+
"step": 220
|
| 407 |
+
},
|
| 408 |
+
{
|
| 409 |
+
"epoch": 3.125,
|
| 410 |
+
"grad_norm": 0.36420342326164246,
|
| 411 |
+
"learning_rate": 2.2176681260642438e-05,
|
| 412 |
+
"loss": 0.0634,
|
| 413 |
+
"mean_token_accuracy": 0.9762553215026856,
|
| 414 |
+
"num_tokens": 14485491.0,
|
| 415 |
+
"step": 225
|
| 416 |
+
},
|
| 417 |
+
{
|
| 418 |
+
"epoch": 3.1944444444444446,
|
| 419 |
+
"grad_norm": 0.2783300578594208,
|
| 420 |
+
"learning_rate": 2.1673869318791425e-05,
|
| 421 |
+
"loss": 0.0621,
|
| 422 |
+
"mean_token_accuracy": 0.9781804919242859,
|
| 423 |
+
"num_tokens": 14813368.0,
|
| 424 |
+
"step": 230
|
| 425 |
+
},
|
| 426 |
+
{
|
| 427 |
+
"epoch": 3.263888888888889,
|
| 428 |
+
"grad_norm": 0.35492244362831116,
|
| 429 |
+
"learning_rate": 2.117135256395068e-05,
|
| 430 |
+
"loss": 0.0616,
|
| 431 |
+
"mean_token_accuracy": 0.9777081608772278,
|
| 432 |
+
"num_tokens": 15134125.0,
|
| 433 |
+
"step": 235
|
| 434 |
+
},
|
| 435 |
+
{
|
| 436 |
+
"epoch": 3.3333333333333335,
|
| 437 |
+
"grad_norm": 0.42209485173225403,
|
| 438 |
+
"learning_rate": 2.0669868508754178e-05,
|
| 439 |
+
"loss": 0.0546,
|
| 440 |
+
"mean_token_accuracy": 0.978722333908081,
|
| 441 |
+
"num_tokens": 15454632.0,
|
| 442 |
+
"step": 240
|
| 443 |
+
},
|
| 444 |
+
{
|
| 445 |
+
"epoch": 3.4027777777777777,
|
| 446 |
+
"grad_norm": 0.4834480583667755,
|
| 447 |
+
"learning_rate": 2.0170153150206755e-05,
|
| 448 |
+
"loss": 0.0655,
|
| 449 |
+
"mean_token_accuracy": 0.978796124458313,
|
| 450 |
+
"num_tokens": 15773802.0,
|
| 451 |
+
"step": 245
|
| 452 |
+
},
|
| 453 |
+
{
|
| 454 |
+
"epoch": 3.4722222222222223,
|
| 455 |
+
"grad_norm": 0.2575581967830658,
|
| 456 |
+
"learning_rate": 1.967293988950703e-05,
|
| 457 |
+
"loss": 0.0594,
|
| 458 |
+
"mean_token_accuracy": 0.9778955817222595,
|
| 459 |
+
"num_tokens": 16098651.0,
|
| 460 |
+
"step": 250
|
| 461 |
+
},
|
| 462 |
+
{
|
| 463 |
+
"epoch": 3.5416666666666665,
|
| 464 |
+
"grad_norm": 0.3081090748310089,
|
| 465 |
+
"learning_rate": 1.9178958455679977e-05,
|
| 466 |
+
"loss": 0.0568,
|
| 467 |
+
"mean_token_accuracy": 0.9780836462974548,
|
| 468 |
+
"num_tokens": 16423293.0,
|
| 469 |
+
"step": 255
|
| 470 |
+
},
|
| 471 |
+
{
|
| 472 |
+
"epoch": 3.611111111111111,
|
| 473 |
+
"grad_norm": 0.22595608234405518,
|
| 474 |
+
"learning_rate": 1.868893383459897e-05,
|
| 475 |
+
"loss": 0.0597,
|
| 476 |
+
"mean_token_accuracy": 0.9756160259246827,
|
| 477 |
+
"num_tokens": 16751938.0,
|
| 478 |
+
"step": 260
|
| 479 |
+
},
|
| 480 |
+
{
|
| 481 |
+
"epoch": 3.6805555555555554,
|
| 482 |
+
"grad_norm": 0.397429496049881,
|
| 483 |
+
"learning_rate": 1.820358520496905e-05,
|
| 484 |
+
"loss": 0.0608,
|
| 485 |
+
"mean_token_accuracy": 0.9785622119903564,
|
| 486 |
+
"num_tokens": 17070894.0,
|
| 487 |
+
"step": 265
|
| 488 |
+
},
|
| 489 |
+
{
|
| 490 |
+
"epoch": 3.75,
|
| 491 |
+
"grad_norm": 0.28394079208374023,
|
| 492 |
+
"learning_rate": 1.772362488283299e-05,
|
| 493 |
+
"loss": 0.0595,
|
| 494 |
+
"mean_token_accuracy": 0.9793779969215393,
|
| 495 |
+
"num_tokens": 17386694.0,
|
| 496 |
+
"step": 270
|
| 497 |
+
},
|
| 498 |
+
{
|
| 499 |
+
"epoch": 3.8194444444444446,
|
| 500 |
+
"grad_norm": 0.27272671461105347,
|
| 501 |
+
"learning_rate": 1.724975727614928e-05,
|
| 502 |
+
"loss": 0.0613,
|
| 503 |
+
"mean_token_accuracy": 0.9769317388534546,
|
| 504 |
+
"num_tokens": 17712906.0,
|
| 505 |
+
"step": 275
|
| 506 |
+
},
|
| 507 |
+
{
|
| 508 |
+
"epoch": 3.888888888888889,
|
| 509 |
+
"grad_norm": 0.2596876919269562,
|
| 510 |
+
"learning_rate": 1.6782677850976294e-05,
|
| 511 |
+
"loss": 0.0592,
|
| 512 |
+
"mean_token_accuracy": 0.9769395232200623,
|
| 513 |
+
"num_tokens": 18034448.0,
|
| 514 |
+
"step": 280
|
| 515 |
+
},
|
| 516 |
+
{
|
| 517 |
+
"epoch": 3.9583333333333335,
|
| 518 |
+
"grad_norm": 0.37678053975105286,
|
| 519 |
+
"learning_rate": 1.632307211077998e-05,
|
| 520 |
+
"loss": 0.058,
|
| 521 |
+
"mean_token_accuracy": 0.9776347041130066,
|
| 522 |
+
"num_tokens": 18351515.0,
|
| 523 |
+
"step": 285
|
| 524 |
+
},
|
| 525 |
+
{
|
| 526 |
+
"epoch": 4.027777777777778,
|
| 527 |
+
"grad_norm": 0.1913955807685852,
|
| 528 |
+
"learning_rate": 1.5871614590362954e-05,
|
| 529 |
+
"loss": 0.0494,
|
| 530 |
+
"mean_token_accuracy": 0.9802444696426391,
|
| 531 |
+
"num_tokens": 18669130.0,
|
| 532 |
+
"step": 290
|
| 533 |
+
},
|
| 534 |
+
{
|
| 535 |
+
"epoch": 4.097222222222222,
|
| 536 |
+
"grad_norm": 0.27026042342185974,
|
| 537 |
+
"learning_rate": 1.5428967865891696e-05,
|
| 538 |
+
"loss": 0.0372,
|
| 539 |
+
"mean_token_accuracy": 0.9868873596191406,
|
| 540 |
+
"num_tokens": 18996467.0,
|
| 541 |
+
"step": 295
|
| 542 |
+
},
|
| 543 |
+
{
|
| 544 |
+
"epoch": 4.166666666666667,
|
| 545 |
+
"grad_norm": 0.17194271087646484,
|
| 546 |
+
"learning_rate": 1.4995781582474628e-05,
|
| 547 |
+
"loss": 0.0379,
|
| 548 |
+
"mean_token_accuracy": 0.9847923636436462,
|
| 549 |
+
"num_tokens": 19323281.0,
|
| 550 |
+
"step": 300
|
| 551 |
+
},
|
| 552 |
+
{
|
| 553 |
+
"epoch": 4.236111111111111,
|
| 554 |
+
"grad_norm": 0.448048859834671,
|
| 555 |
+
"learning_rate": 1.4572691500718359e-05,
|
| 556 |
+
"loss": 0.0418,
|
| 557 |
+
"mean_token_accuracy": 0.9859732508659362,
|
| 558 |
+
"num_tokens": 19652166.0,
|
| 559 |
+
"step": 305
|
| 560 |
+
},
|
| 561 |
+
{
|
| 562 |
+
"epoch": 4.305555555555555,
|
| 563 |
+
"grad_norm": 0.18234789371490479,
|
| 564 |
+
"learning_rate": 1.4160318563661293e-05,
|
| 565 |
+
"loss": 0.035,
|
| 566 |
+
"mean_token_accuracy": 0.9862746596336365,
|
| 567 |
+
"num_tokens": 19976780.0,
|
| 568 |
+
"step": 310
|
| 569 |
+
},
|
| 570 |
+
{
|
| 571 |
+
"epoch": 4.375,
|
| 572 |
+
"grad_norm": 0.28801319003105164,
|
| 573 |
+
"learning_rate": 1.3759267985454126e-05,
|
| 574 |
+
"loss": 0.04,
|
| 575 |
+
"mean_token_accuracy": 0.9853678345680237,
|
| 576 |
+
"num_tokens": 20294045.0,
|
| 577 |
+
"step": 315
|
| 578 |
+
},
|
| 579 |
+
{
|
| 580 |
+
"epoch": 4.444444444444445,
|
| 581 |
+
"grad_norm": 0.20915500819683075,
|
| 582 |
+
"learning_rate": 1.3370128363124604e-05,
|
| 583 |
+
"loss": 0.0424,
|
| 584 |
+
"mean_token_accuracy": 0.9826555609703064,
|
| 585 |
+
"num_tokens": 20620135.0,
|
| 586 |
+
"step": 320
|
| 587 |
+
},
|
| 588 |
+
{
|
| 589 |
+
"epoch": 4.513888888888889,
|
| 590 |
+
"grad_norm": 0.17628608644008636,
|
| 591 |
+
"learning_rate": 1.2993470812730217e-05,
|
| 592 |
+
"loss": 0.0385,
|
| 593 |
+
"mean_token_accuracy": 0.9821347594261169,
|
| 594 |
+
"num_tokens": 20941710.0,
|
| 595 |
+
"step": 325
|
| 596 |
+
},
|
| 597 |
+
{
|
| 598 |
+
"epoch": 4.583333333333333,
|
| 599 |
+
"grad_norm": 0.23610952496528625,
|
| 600 |
+
"learning_rate": 1.2629848131166632e-05,
|
| 601 |
+
"loss": 0.0333,
|
| 602 |
+
"mean_token_accuracy": 0.9875306367874146,
|
| 603 |
+
"num_tokens": 21256388.0,
|
| 604 |
+
"step": 330
|
| 605 |
+
},
|
| 606 |
+
{
|
| 607 |
+
"epoch": 4.652777777777778,
|
| 608 |
+
"grad_norm": 0.18080389499664307,
|
| 609 |
+
"learning_rate": 1.2279793984862026e-05,
|
| 610 |
+
"loss": 0.0371,
|
| 611 |
+
"mean_token_accuracy": 0.9843253016471862,
|
| 612 |
+
"num_tokens": 21579073.0,
|
| 613 |
+
"step": 335
|
| 614 |
+
},
|
| 615 |
+
{
|
| 616 |
+
"epoch": 4.722222222222222,
|
| 617 |
+
"grad_norm": 0.20831552147865295,
|
| 618 |
+
"learning_rate": 1.1943822126548e-05,
|
| 619 |
+
"loss": 0.0378,
|
| 620 |
+
"mean_token_accuracy": 0.9837713360786438,
|
| 621 |
+
"num_tokens": 21904012.0,
|
| 622 |
+
"step": 340
|
| 623 |
+
},
|
| 624 |
+
{
|
| 625 |
+
"epoch": 4.791666666666667,
|
| 626 |
+
"grad_norm": 0.31704482436180115,
|
| 627 |
+
"learning_rate": 1.1622425641256605e-05,
|
| 628 |
+
"loss": 0.0428,
|
| 629 |
+
"mean_token_accuracy": 0.9829642415046692,
|
| 630 |
+
"num_tokens": 22224825.0,
|
| 631 |
+
"step": 345
|
| 632 |
+
},
|
| 633 |
+
{
|
| 634 |
+
"epoch": 4.861111111111111,
|
| 635 |
+
"grad_norm": 0.2652062773704529,
|
| 636 |
+
"learning_rate": 1.1316076222650062e-05,
|
| 637 |
+
"loss": 0.0343,
|
| 638 |
+
"mean_token_accuracy": 0.9869701027870178,
|
| 639 |
+
"num_tokens": 22536397.0,
|
| 640 |
+
"step": 350
|
| 641 |
+
},
|
| 642 |
+
{
|
| 643 |
+
"epoch": 4.930555555555555,
|
| 644 |
+
"grad_norm": 0.3284396529197693,
|
| 645 |
+
"learning_rate": 1.102522348074526e-05,
|
| 646 |
+
"loss": 0.0368,
|
| 647 |
+
"mean_token_accuracy": 0.9868231415748596,
|
| 648 |
+
"num_tokens": 22852514.0,
|
| 649 |
+
"step": 355
|
| 650 |
+
},
|
| 651 |
+
{
|
| 652 |
+
"epoch": 5.0,
|
| 653 |
+
"grad_norm": 0.12725569307804108,
|
| 654 |
+
"learning_rate": 1.0750294282049076e-05,
|
| 655 |
+
"loss": 0.0375,
|
| 656 |
+
"mean_token_accuracy": 0.9843321442604065,
|
| 657 |
+
"num_tokens": 23174822.0,
|
| 658 |
+
"step": 360
|
| 659 |
+
},
|
| 660 |
+
{
|
| 661 |
+
"epoch": 5.069444444444445,
|
| 662 |
+
"grad_norm": 0.12493331730365753,
|
| 663 |
+
"learning_rate": 1.0491692123072876e-05,
|
| 664 |
+
"loss": 0.0264,
|
| 665 |
+
"mean_token_accuracy": 0.9897792339324951,
|
| 666 |
+
"num_tokens": 23497420.0,
|
| 667 |
+
"step": 365
|
| 668 |
+
},
|
| 669 |
+
{
|
| 670 |
+
"epoch": 5.138888888888889,
|
| 671 |
+
"grad_norm": 0.19263431429862976,
|
| 672 |
+
"learning_rate": 1.0249796538145782e-05,
|
| 673 |
+
"loss": 0.0296,
|
| 674 |
+
"mean_token_accuracy": 0.9884816765785217,
|
| 675 |
+
"num_tokens": 23825885.0,
|
| 676 |
+
"step": 370
|
| 677 |
+
},
|
| 678 |
+
{
|
| 679 |
+
"epoch": 5.208333333333333,
|
| 680 |
+
"grad_norm": 0.25486940145492554,
|
| 681 |
+
"learning_rate": 1.002496254239568e-05,
|
| 682 |
+
"loss": 0.0247,
|
| 683 |
+
"mean_token_accuracy": 0.9909913301467895,
|
| 684 |
+
"num_tokens": 24147773.0,
|
| 685 |
+
"step": 375
|
| 686 |
+
},
|
| 687 |
+
{
|
| 688 |
+
"epoch": 5.277777777777778,
|
| 689 |
+
"grad_norm": 0.23300352692604065,
|
| 690 |
+
"learning_rate": 9.817520110715585e-06,
|
| 691 |
+
"loss": 0.0197,
|
| 692 |
+
"mean_token_accuracy": 0.992484164237976,
|
| 693 |
+
"num_tokens": 24469253.0,
|
| 694 |
+
"step": 380
|
| 695 |
+
},
|
| 696 |
+
{
|
| 697 |
+
"epoch": 5.347222222222222,
|
| 698 |
+
"grad_norm": 0.291847288608551,
|
| 699 |
+
"learning_rate": 9.627773693479954e-06,
|
| 700 |
+
"loss": 0.0254,
|
| 701 |
+
"mean_token_accuracy": 0.9914757132530212,
|
| 702 |
+
"num_tokens": 24790062.0,
|
| 703 |
+
"step": 385
|
| 704 |
+
},
|
| 705 |
+
{
|
| 706 |
+
"epoch": 5.416666666666667,
|
| 707 |
+
"grad_norm": 0.2282291054725647,
|
| 708 |
+
"learning_rate": 9.45600176972181e-06,
|
| 709 |
+
"loss": 0.0232,
|
| 710 |
+
"mean_token_accuracy": 0.9907638549804687,
|
| 711 |
+
"num_tokens": 25109161.0,
|
| 712 |
+
"step": 390
|
| 713 |
+
},
|
| 714 |
+
{
|
| 715 |
+
"epoch": 5.486111111111111,
|
| 716 |
+
"grad_norm": 0.22575975954532623,
|
| 717 |
+
"learning_rate": 9.302456438426336e-06,
|
| 718 |
+
"loss": 0.0239,
|
| 719 |
+
"mean_token_accuracy": 0.991183590888977,
|
| 720 |
+
"num_tokens": 25429823.0,
|
| 721 |
+
"step": 395
|
| 722 |
+
},
|
| 723 |
+
{
|
| 724 |
+
"epoch": 5.555555555555555,
|
| 725 |
+
"grad_norm": 0.2374185472726822,
|
| 726 |
+
"learning_rate": 9.167363048540858e-06,
|
| 727 |
+
"loss": 0.0256,
|
| 728 |
+
"mean_token_accuracy": 0.9888947367668152,
|
| 729 |
+
"num_tokens": 25755989.0,
|
| 730 |
+
"step": 400
|
| 731 |
+
},
|
| 732 |
+
{
|
| 733 |
+
"epoch": 5.625,
|
| 734 |
+
"grad_norm": 0.14167584478855133,
|
| 735 |
+
"learning_rate": 9.0509198682442e-06,
|
| 736 |
+
"loss": 0.0233,
|
| 737 |
+
"mean_token_accuracy": 0.9902876257896424,
|
| 738 |
+
"num_tokens": 26069656.0,
|
| 739 |
+
"step": 405
|
| 740 |
+
},
|
| 741 |
+
{
|
| 742 |
+
"epoch": 5.694444444444445,
|
| 743 |
+
"grad_norm": 0.19081205129623413,
|
| 744 |
+
"learning_rate": 8.953297793960764e-06,
|
| 745 |
+
"loss": 0.0228,
|
| 746 |
+
"mean_token_accuracy": 0.99054856300354,
|
| 747 |
+
"num_tokens": 26386466.0,
|
| 748 |
+
"step": 410
|
| 749 |
+
},
|
| 750 |
+
{
|
| 751 |
+
"epoch": 5.763888888888889,
|
| 752 |
+
"grad_norm": 0.2015998363494873,
|
| 753 |
+
"learning_rate": 8.874640099546494e-06,
|
| 754 |
+
"loss": 0.0304,
|
| 755 |
+
"mean_token_accuracy": 0.9869679093360901,
|
| 756 |
+
"num_tokens": 26716123.0,
|
| 757 |
+
"step": 415
|
| 758 |
+
},
|
| 759 |
+
{
|
| 760 |
+
"epoch": 5.833333333333333,
|
| 761 |
+
"grad_norm": 0.2091236114501953,
|
| 762 |
+
"learning_rate": 8.815062226014707e-06,
|
| 763 |
+
"loss": 0.0266,
|
| 764 |
+
"mean_token_accuracy": 0.9901867628097534,
|
| 765 |
+
"num_tokens": 27032695.0,
|
| 766 |
+
"step": 420
|
| 767 |
+
},
|
| 768 |
+
{
|
| 769 |
+
"epoch": 5.902777777777778,
|
| 770 |
+
"grad_norm": 0.30149850249290466,
|
| 771 |
+
"learning_rate": 8.774651612110506e-06,
|
| 772 |
+
"loss": 0.0315,
|
| 773 |
+
"mean_token_accuracy": 0.9872185707092285,
|
| 774 |
+
"num_tokens": 27354910.0,
|
| 775 |
+
"step": 425
|
| 776 |
+
}
|
| 777 |
+
],
|
| 778 |
+
"logging_steps": 5,
|
| 779 |
+
"max_steps": 432,
|
| 780 |
+
"num_input_tokens_seen": 0,
|
| 781 |
+
"num_train_epochs": 6,
|
| 782 |
+
"save_steps": 500,
|
| 783 |
+
"stateful_callbacks": {
|
| 784 |
+
"TrainerControl": {
|
| 785 |
+
"args": {
|
| 786 |
+
"should_epoch_stop": false,
|
| 787 |
+
"should_evaluate": false,
|
| 788 |
+
"should_log": false,
|
| 789 |
+
"should_save": true,
|
| 790 |
+
"should_training_stop": false
|
| 791 |
+
},
|
| 792 |
+
"attributes": {}
|
| 793 |
+
}
|
| 794 |
+
},
|
| 795 |
+
"total_flos": 1.1898096215025254e+18,
|
| 796 |
+
"train_batch_size": 28,
|
| 797 |
+
"trial_name": null,
|
| 798 |
+
"trial_params": null
|
| 799 |
+
}
|
training_args.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:aa974c06d9c990dbcaf84d0c9e79b9cf82adbff3b23e43560f4aeddc76dda1e4
|
| 3 |
+
size 6417
|