Instructions to use staerkjo/checkpoints-mistral with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use staerkjo/checkpoints-mistral with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Ministral-8B-Instruct-2410") model = PeftModel.from_pretrained(base_model, "staerkjo/checkpoints-mistral") - Transformers
How to use staerkjo/checkpoints-mistral with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="staerkjo/checkpoints-mistral") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("staerkjo/checkpoints-mistral", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use staerkjo/checkpoints-mistral with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "staerkjo/checkpoints-mistral" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "staerkjo/checkpoints-mistral", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/staerkjo/checkpoints-mistral
- SGLang
How to use staerkjo/checkpoints-mistral 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 "staerkjo/checkpoints-mistral" \ --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": "staerkjo/checkpoints-mistral", "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 "staerkjo/checkpoints-mistral" \ --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": "staerkjo/checkpoints-mistral", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Unsloth Studio
How to use staerkjo/checkpoints-mistral with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for staerkjo/checkpoints-mistral to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for staerkjo/checkpoints-mistral to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for staerkjo/checkpoints-mistral to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="staerkjo/checkpoints-mistral", max_seq_length=2048, ) - Docker Model Runner
How to use staerkjo/checkpoints-mistral with Docker Model Runner:
docker model run hf.co/staerkjo/checkpoints-mistral
Upload folder using huggingface_hub
Browse files- README.md +200 -12
- adapter_config.json +4 -4
- adapter_model.safetensors +1 -1
- optimizer.pt +3 -0
- rng_state.pth +3 -0
- scheduler.pt +3 -0
- trainer_state.json +564 -0
- training_args.bin +3 -0
README.md
CHANGED
|
@@ -1,22 +1,210 @@
|
|
| 1 |
---
|
| 2 |
base_model: mistralai/Ministral-8B-Instruct-2410
|
|
|
|
|
|
|
| 3 |
tags:
|
| 4 |
-
-
|
|
|
|
|
|
|
| 5 |
- transformers
|
| 6 |
-
- unsloth
|
| 7 |
-
- ministral
|
| 8 |
- trl
|
| 9 |
-
|
| 10 |
-
language:
|
| 11 |
-
- en
|
| 12 |
---
|
| 13 |
|
| 14 |
-
#
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 15 |
|
| 16 |
-
|
| 17 |
-
- **License:** apache-2.0
|
| 18 |
-
- **Finetuned from model :** mistralai/Ministral-8B-Instruct-2410
|
| 19 |
|
| 20 |
-
|
|
|
|
| 21 |
|
| 22 |
-
|
|
|
|
| 1 |
---
|
| 2 |
base_model: mistralai/Ministral-8B-Instruct-2410
|
| 3 |
+
library_name: peft
|
| 4 |
+
pipeline_tag: text-generation
|
| 5 |
tags:
|
| 6 |
+
- base_model:adapter:mistralai/Ministral-8B-Instruct-2410
|
| 7 |
+
- lora
|
| 8 |
+
- sft
|
| 9 |
- transformers
|
|
|
|
|
|
|
| 10 |
- trl
|
| 11 |
+
- unsloth
|
|
|
|
|
|
|
| 12 |
---
|
| 13 |
|
| 14 |
+
# Model Card for Model ID
|
| 15 |
+
|
| 16 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
|
| 20 |
+
## Model Details
|
| 21 |
+
|
| 22 |
+
### Model Description
|
| 23 |
+
|
| 24 |
+
<!-- Provide a longer summary of what this model is. -->
|
| 25 |
+
|
| 26 |
+
|
| 27 |
+
|
| 28 |
+
- **Developed by:** [More Information Needed]
|
| 29 |
+
- **Funded by [optional]:** [More Information Needed]
|
| 30 |
+
- **Shared by [optional]:** [More Information Needed]
|
| 31 |
+
- **Model type:** [More Information Needed]
|
| 32 |
+
- **Language(s) (NLP):** [More Information Needed]
|
| 33 |
+
- **License:** [More Information Needed]
|
| 34 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
| 35 |
+
|
| 36 |
+
### Model Sources [optional]
|
| 37 |
+
|
| 38 |
+
<!-- Provide the basic links for the model. -->
|
| 39 |
+
|
| 40 |
+
- **Repository:** [More Information Needed]
|
| 41 |
+
- **Paper [optional]:** [More Information Needed]
|
| 42 |
+
- **Demo [optional]:** [More Information Needed]
|
| 43 |
+
|
| 44 |
+
## Uses
|
| 45 |
+
|
| 46 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
| 47 |
+
|
| 48 |
+
### Direct Use
|
| 49 |
+
|
| 50 |
+
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
| 51 |
+
|
| 52 |
+
[More Information Needed]
|
| 53 |
+
|
| 54 |
+
### Downstream Use [optional]
|
| 55 |
+
|
| 56 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
| 57 |
+
|
| 58 |
+
[More Information Needed]
|
| 59 |
+
|
| 60 |
+
### Out-of-Scope Use
|
| 61 |
+
|
| 62 |
+
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
| 63 |
+
|
| 64 |
+
[More Information Needed]
|
| 65 |
+
|
| 66 |
+
## Bias, Risks, and Limitations
|
| 67 |
+
|
| 68 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
| 69 |
+
|
| 70 |
+
[More Information Needed]
|
| 71 |
+
|
| 72 |
+
### Recommendations
|
| 73 |
+
|
| 74 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
| 75 |
+
|
| 76 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
| 77 |
+
|
| 78 |
+
## How to Get Started with the Model
|
| 79 |
+
|
| 80 |
+
Use the code below to get started with the model.
|
| 81 |
+
|
| 82 |
+
[More Information Needed]
|
| 83 |
+
|
| 84 |
+
## Training Details
|
| 85 |
+
|
| 86 |
+
### Training Data
|
| 87 |
+
|
| 88 |
+
<!-- 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. -->
|
| 89 |
+
|
| 90 |
+
[More Information Needed]
|
| 91 |
+
|
| 92 |
+
### Training Procedure
|
| 93 |
+
|
| 94 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
| 95 |
+
|
| 96 |
+
#### Preprocessing [optional]
|
| 97 |
+
|
| 98 |
+
[More Information Needed]
|
| 99 |
+
|
| 100 |
+
|
| 101 |
+
#### Training Hyperparameters
|
| 102 |
+
|
| 103 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
| 104 |
+
|
| 105 |
+
#### Speeds, Sizes, Times [optional]
|
| 106 |
+
|
| 107 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
| 108 |
+
|
| 109 |
+
[More Information Needed]
|
| 110 |
+
|
| 111 |
+
## Evaluation
|
| 112 |
+
|
| 113 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
| 114 |
+
|
| 115 |
+
### Testing Data, Factors & Metrics
|
| 116 |
+
|
| 117 |
+
#### Testing Data
|
| 118 |
+
|
| 119 |
+
<!-- This should link to a Dataset Card if possible. -->
|
| 120 |
+
|
| 121 |
+
[More Information Needed]
|
| 122 |
+
|
| 123 |
+
#### Factors
|
| 124 |
+
|
| 125 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
| 126 |
+
|
| 127 |
+
[More Information Needed]
|
| 128 |
+
|
| 129 |
+
#### Metrics
|
| 130 |
+
|
| 131 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
| 132 |
+
|
| 133 |
+
[More Information Needed]
|
| 134 |
+
|
| 135 |
+
### Results
|
| 136 |
+
|
| 137 |
+
[More Information Needed]
|
| 138 |
+
|
| 139 |
+
#### Summary
|
| 140 |
+
|
| 141 |
+
|
| 142 |
+
|
| 143 |
+
## Model Examination [optional]
|
| 144 |
+
|
| 145 |
+
<!-- Relevant interpretability work for the model goes here -->
|
| 146 |
+
|
| 147 |
+
[More Information Needed]
|
| 148 |
+
|
| 149 |
+
## Environmental Impact
|
| 150 |
+
|
| 151 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
| 152 |
+
|
| 153 |
+
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).
|
| 154 |
+
|
| 155 |
+
- **Hardware Type:** [More Information Needed]
|
| 156 |
+
- **Hours used:** [More Information Needed]
|
| 157 |
+
- **Cloud Provider:** [More Information Needed]
|
| 158 |
+
- **Compute Region:** [More Information Needed]
|
| 159 |
+
- **Carbon Emitted:** [More Information Needed]
|
| 160 |
+
|
| 161 |
+
## Technical Specifications [optional]
|
| 162 |
+
|
| 163 |
+
### Model Architecture and Objective
|
| 164 |
+
|
| 165 |
+
[More Information Needed]
|
| 166 |
+
|
| 167 |
+
### Compute Infrastructure
|
| 168 |
+
|
| 169 |
+
[More Information Needed]
|
| 170 |
+
|
| 171 |
+
#### Hardware
|
| 172 |
+
|
| 173 |
+
[More Information Needed]
|
| 174 |
+
|
| 175 |
+
#### Software
|
| 176 |
+
|
| 177 |
+
[More Information Needed]
|
| 178 |
+
|
| 179 |
+
## Citation [optional]
|
| 180 |
+
|
| 181 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
| 182 |
+
|
| 183 |
+
**BibTeX:**
|
| 184 |
+
|
| 185 |
+
[More Information Needed]
|
| 186 |
+
|
| 187 |
+
**APA:**
|
| 188 |
+
|
| 189 |
+
[More Information Needed]
|
| 190 |
+
|
| 191 |
+
## Glossary [optional]
|
| 192 |
+
|
| 193 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
| 194 |
+
|
| 195 |
+
[More Information Needed]
|
| 196 |
+
|
| 197 |
+
## More Information [optional]
|
| 198 |
+
|
| 199 |
+
[More Information Needed]
|
| 200 |
+
|
| 201 |
+
## Model Card Authors [optional]
|
| 202 |
+
|
| 203 |
+
[More Information Needed]
|
| 204 |
|
| 205 |
+
## Model Card Contact
|
|
|
|
|
|
|
| 206 |
|
| 207 |
+
[More Information Needed]
|
| 208 |
+
### Framework versions
|
| 209 |
|
| 210 |
+
- PEFT 0.18.1
|
adapter_config.json
CHANGED
|
@@ -33,13 +33,13 @@
|
|
| 33 |
"rank_pattern": {},
|
| 34 |
"revision": null,
|
| 35 |
"target_modules": [
|
|
|
|
|
|
|
| 36 |
"up_proj",
|
| 37 |
-
"o_proj",
|
| 38 |
"k_proj",
|
|
|
|
| 39 |
"gate_proj",
|
| 40 |
-
"
|
| 41 |
-
"down_proj",
|
| 42 |
-
"v_proj"
|
| 43 |
],
|
| 44 |
"target_parameters": null,
|
| 45 |
"task_type": "CAUSAL_LM",
|
|
|
|
| 33 |
"rank_pattern": {},
|
| 34 |
"revision": null,
|
| 35 |
"target_modules": [
|
| 36 |
+
"down_proj",
|
| 37 |
+
"q_proj",
|
| 38 |
"up_proj",
|
|
|
|
| 39 |
"k_proj",
|
| 40 |
+
"v_proj",
|
| 41 |
"gate_proj",
|
| 42 |
+
"o_proj"
|
|
|
|
|
|
|
| 43 |
],
|
| 44 |
"target_parameters": null,
|
| 45 |
"task_type": "CAUSAL_LM",
|
adapter_model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 174655536
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:8288278b0e8753968d77bf1c8336d60cc14e47f5e1f002a2098e12ffc5312180
|
| 3 |
size 174655536
|
optimizer.pt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:f6a592a2ee94780e2f2380ba303da2cd752d7a9aef2bb95c1c0361aca9f6b9ab
|
| 3 |
+
size 89256133
|
rng_state.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:4801416a03beb0f63c300670679d3fb6cca48da8259362e9be9e6ffae0c5ffd0
|
| 3 |
+
size 14645
|
scheduler.pt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:3004f7825159b269b51901bed48537be99aba8283a971260c5ed4733dfbc8ad7
|
| 3 |
+
size 1465
|
trainer_state.json
ADDED
|
@@ -0,0 +1,564 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"best_global_step": 2000,
|
| 3 |
+
"best_metric": 0.2992326021194458,
|
| 4 |
+
"best_model_checkpoint": "./outputs/checkpoints/checkpoint-2000",
|
| 5 |
+
"epoch": 3.0,
|
| 6 |
+
"eval_steps": 250,
|
| 7 |
+
"global_step": 3117,
|
| 8 |
+
"is_hyper_param_search": false,
|
| 9 |
+
"is_local_process_zero": true,
|
| 10 |
+
"is_world_process_zero": true,
|
| 11 |
+
"log_history": [
|
| 12 |
+
{
|
| 13 |
+
"epoch": 0.04814636494944632,
|
| 14 |
+
"grad_norm": 0.49752116203308105,
|
| 15 |
+
"learning_rate": 6.32258064516129e-05,
|
| 16 |
+
"loss": 1.477303009033203,
|
| 17 |
+
"step": 50
|
| 18 |
+
},
|
| 19 |
+
{
|
| 20 |
+
"epoch": 0.09629272989889263,
|
| 21 |
+
"grad_norm": 0.3652721643447876,
|
| 22 |
+
"learning_rate": 0.00012774193548387096,
|
| 23 |
+
"loss": 0.46554481506347656,
|
| 24 |
+
"step": 100
|
| 25 |
+
},
|
| 26 |
+
{
|
| 27 |
+
"epoch": 0.14443909484833894,
|
| 28 |
+
"grad_norm": 0.32378166913986206,
|
| 29 |
+
"learning_rate": 0.00019225806451612904,
|
| 30 |
+
"loss": 0.4035662078857422,
|
| 31 |
+
"step": 150
|
| 32 |
+
},
|
| 33 |
+
{
|
| 34 |
+
"epoch": 0.19258545979778527,
|
| 35 |
+
"grad_norm": 0.3265906870365143,
|
| 36 |
+
"learning_rate": 0.0001998911255002373,
|
| 37 |
+
"loss": 0.38129932403564454,
|
| 38 |
+
"step": 200
|
| 39 |
+
},
|
| 40 |
+
{
|
| 41 |
+
"epoch": 0.2407318247472316,
|
| 42 |
+
"grad_norm": 0.2637921869754791,
|
| 43 |
+
"learning_rate": 0.00019950341273368075,
|
| 44 |
+
"loss": 0.36489856719970704,
|
| 45 |
+
"step": 250
|
| 46 |
+
},
|
| 47 |
+
{
|
| 48 |
+
"epoch": 0.2407318247472316,
|
| 49 |
+
"eval_loss": 0.35290107131004333,
|
| 50 |
+
"eval_runtime": 694.8697,
|
| 51 |
+
"eval_samples_per_second": 2.658,
|
| 52 |
+
"eval_steps_per_second": 0.665,
|
| 53 |
+
"step": 250
|
| 54 |
+
},
|
| 55 |
+
{
|
| 56 |
+
"epoch": 0.2888781896966779,
|
| 57 |
+
"grad_norm": 0.23706986010074615,
|
| 58 |
+
"learning_rate": 0.00019883592694304428,
|
| 59 |
+
"loss": 0.3474379348754883,
|
| 60 |
+
"step": 300
|
| 61 |
+
},
|
| 62 |
+
{
|
| 63 |
+
"epoch": 0.33702455464612424,
|
| 64 |
+
"grad_norm": 0.2362891435623169,
|
| 65 |
+
"learning_rate": 0.00019789054489328546,
|
| 66 |
+
"loss": 0.35004573822021484,
|
| 67 |
+
"step": 350
|
| 68 |
+
},
|
| 69 |
+
{
|
| 70 |
+
"epoch": 0.38517091959557054,
|
| 71 |
+
"grad_norm": 0.2134203463792801,
|
| 72 |
+
"learning_rate": 0.00019666992470825862,
|
| 73 |
+
"loss": 0.33882694244384765,
|
| 74 |
+
"step": 400
|
| 75 |
+
},
|
| 76 |
+
{
|
| 77 |
+
"epoch": 0.43331728454501683,
|
| 78 |
+
"grad_norm": 0.23494897782802582,
|
| 79 |
+
"learning_rate": 0.0001951774983968872,
|
| 80 |
+
"loss": 0.35397193908691404,
|
| 81 |
+
"step": 450
|
| 82 |
+
},
|
| 83 |
+
{
|
| 84 |
+
"epoch": 0.4814636494944632,
|
| 85 |
+
"grad_norm": 0.20449194312095642,
|
| 86 |
+
"learning_rate": 0.00019341746220340924,
|
| 87 |
+
"loss": 0.3447082901000977,
|
| 88 |
+
"step": 500
|
| 89 |
+
},
|
| 90 |
+
{
|
| 91 |
+
"epoch": 0.4814636494944632,
|
| 92 |
+
"eval_loss": 0.3319753110408783,
|
| 93 |
+
"eval_runtime": 695.9468,
|
| 94 |
+
"eval_samples_per_second": 2.654,
|
| 95 |
+
"eval_steps_per_second": 0.664,
|
| 96 |
+
"step": 500
|
| 97 |
+
},
|
| 98 |
+
{
|
| 99 |
+
"epoch": 0.5296100144439095,
|
| 100 |
+
"grad_norm": 0.19552361965179443,
|
| 101 |
+
"learning_rate": 0.00019139476480882785,
|
| 102 |
+
"loss": 0.34256481170654296,
|
| 103 |
+
"step": 550
|
| 104 |
+
},
|
| 105 |
+
{
|
| 106 |
+
"epoch": 0.5777563793933558,
|
| 107 |
+
"grad_norm": 0.19304735958576202,
|
| 108 |
+
"learning_rate": 0.00018911509341674071,
|
| 109 |
+
"loss": 0.3311490631103516,
|
| 110 |
+
"step": 600
|
| 111 |
+
},
|
| 112 |
+
{
|
| 113 |
+
"epoch": 0.6259027443428021,
|
| 114 |
+
"grad_norm": 0.22191040217876434,
|
| 115 |
+
"learning_rate": 0.00018658485776267095,
|
| 116 |
+
"loss": 0.32927177429199217,
|
| 117 |
+
"step": 650
|
| 118 |
+
},
|
| 119 |
+
{
|
| 120 |
+
"epoch": 0.6740491092922485,
|
| 121 |
+
"grad_norm": 0.19663718342781067,
|
| 122 |
+
"learning_rate": 0.00018381117209186033,
|
| 123 |
+
"loss": 0.32792991638183594,
|
| 124 |
+
"step": 700
|
| 125 |
+
},
|
| 126 |
+
{
|
| 127 |
+
"epoch": 0.7221954742416947,
|
| 128 |
+
"grad_norm": 0.20722714066505432,
|
| 129 |
+
"learning_rate": 0.00018080183515619726,
|
| 130 |
+
"loss": 0.3278979873657227,
|
| 131 |
+
"step": 750
|
| 132 |
+
},
|
| 133 |
+
{
|
| 134 |
+
"epoch": 0.7221954742416947,
|
| 135 |
+
"eval_loss": 0.3201846480369568,
|
| 136 |
+
"eval_runtime": 698.1861,
|
| 137 |
+
"eval_samples_per_second": 2.645,
|
| 138 |
+
"eval_steps_per_second": 0.662,
|
| 139 |
+
"step": 750
|
| 140 |
+
},
|
| 141 |
+
{
|
| 142 |
+
"epoch": 0.7703418391911411,
|
| 143 |
+
"grad_norm": 0.18782874941825867,
|
| 144 |
+
"learning_rate": 0.000177565308286523,
|
| 145 |
+
"loss": 0.32439987182617186,
|
| 146 |
+
"step": 800
|
| 147 |
+
},
|
| 148 |
+
{
|
| 149 |
+
"epoch": 0.8184882041405874,
|
| 150 |
+
"grad_norm": 0.19059380888938904,
|
| 151 |
+
"learning_rate": 0.0001741106916019688,
|
| 152 |
+
"loss": 0.32634170532226564,
|
| 153 |
+
"step": 850
|
| 154 |
+
},
|
| 155 |
+
{
|
| 156 |
+
"epoch": 0.8666345690900337,
|
| 157 |
+
"grad_norm": 0.19336679577827454,
|
| 158 |
+
"learning_rate": 0.00017044769842321705,
|
| 159 |
+
"loss": 0.3187075614929199,
|
| 160 |
+
"step": 900
|
| 161 |
+
},
|
| 162 |
+
{
|
| 163 |
+
"epoch": 0.91478093403948,
|
| 164 |
+
"grad_norm": 0.19474540650844574,
|
| 165 |
+
"learning_rate": 0.00016658662796162794,
|
| 166 |
+
"loss": 0.3124076271057129,
|
| 167 |
+
"step": 950
|
| 168 |
+
},
|
| 169 |
+
{
|
| 170 |
+
"epoch": 0.9629272989889264,
|
| 171 |
+
"grad_norm": 0.19545841217041016,
|
| 172 |
+
"learning_rate": 0.0001625383363610215,
|
| 173 |
+
"loss": 0.32053829193115235,
|
| 174 |
+
"step": 1000
|
| 175 |
+
},
|
| 176 |
+
{
|
| 177 |
+
"epoch": 0.9629272989889264,
|
| 178 |
+
"eval_loss": 0.3141631782054901,
|
| 179 |
+
"eval_runtime": 696.8814,
|
| 180 |
+
"eval_samples_per_second": 2.65,
|
| 181 |
+
"eval_steps_per_second": 0.663,
|
| 182 |
+
"step": 1000
|
| 183 |
+
},
|
| 184 |
+
{
|
| 185 |
+
"epoch": 1.010592200288878,
|
| 186 |
+
"grad_norm": 0.23214930295944214,
|
| 187 |
+
"learning_rate": 0.00015831420617353685,
|
| 188 |
+
"loss": 0.3157562255859375,
|
| 189 |
+
"step": 1050
|
| 190 |
+
},
|
| 191 |
+
{
|
| 192 |
+
"epoch": 1.0587385652383245,
|
| 193 |
+
"grad_norm": 0.19467434287071228,
|
| 194 |
+
"learning_rate": 0.0001539261143553928,
|
| 195 |
+
"loss": 0.29116039276123046,
|
| 196 |
+
"step": 1100
|
| 197 |
+
},
|
| 198 |
+
{
|
| 199 |
+
"epoch": 1.1068849301877708,
|
| 200 |
+
"grad_norm": 0.2111353874206543,
|
| 201 |
+
"learning_rate": 0.0001493863988725362,
|
| 202 |
+
"loss": 0.29466302871704103,
|
| 203 |
+
"step": 1150
|
| 204 |
+
},
|
| 205 |
+
{
|
| 206 |
+
"epoch": 1.155031295137217,
|
| 207 |
+
"grad_norm": 0.21094423532485962,
|
| 208 |
+
"learning_rate": 0.0001447078240100725,
|
| 209 |
+
"loss": 0.2904193878173828,
|
| 210 |
+
"step": 1200
|
| 211 |
+
},
|
| 212 |
+
{
|
| 213 |
+
"epoch": 1.2031776600866635,
|
| 214 |
+
"grad_norm": 0.20865824818611145,
|
| 215 |
+
"learning_rate": 0.00013990354448301798,
|
| 216 |
+
"loss": 0.29510746002197263,
|
| 217 |
+
"step": 1250
|
| 218 |
+
},
|
| 219 |
+
{
|
| 220 |
+
"epoch": 1.2031776600866635,
|
| 221 |
+
"eval_loss": 0.3110591769218445,
|
| 222 |
+
"eval_runtime": 694.8335,
|
| 223 |
+
"eval_samples_per_second": 2.658,
|
| 224 |
+
"eval_steps_per_second": 0.665,
|
| 225 |
+
"step": 1250
|
| 226 |
+
},
|
| 227 |
+
{
|
| 228 |
+
"epoch": 1.2513240250361097,
|
| 229 |
+
"grad_norm": 0.20231032371520996,
|
| 230 |
+
"learning_rate": 0.00013498706844928282,
|
| 231 |
+
"loss": 0.29798513412475586,
|
| 232 |
+
"step": 1300
|
| 233 |
+
},
|
| 234 |
+
{
|
| 235 |
+
"epoch": 1.2994703899855562,
|
| 236 |
+
"grad_norm": 0.23587271571159363,
|
| 237 |
+
"learning_rate": 0.00012997221952888146,
|
| 238 |
+
"loss": 0.29837047576904296,
|
| 239 |
+
"step": 1350
|
| 240 |
+
},
|
| 241 |
+
{
|
| 242 |
+
"epoch": 1.3476167549350024,
|
| 243 |
+
"grad_norm": 0.19505874812602997,
|
| 244 |
+
"learning_rate": 0.0001248730979361606,
|
| 245 |
+
"loss": 0.2953862953186035,
|
| 246 |
+
"step": 1400
|
| 247 |
+
},
|
| 248 |
+
{
|
| 249 |
+
"epoch": 1.3957631198844487,
|
| 250 |
+
"grad_norm": 0.18162201344966888,
|
| 251 |
+
"learning_rate": 0.00011970404083432846,
|
| 252 |
+
"loss": 0.28933364868164063,
|
| 253 |
+
"step": 1450
|
| 254 |
+
},
|
| 255 |
+
{
|
| 256 |
+
"epoch": 1.443909484833895,
|
| 257 |
+
"grad_norm": 0.18973521888256073,
|
| 258 |
+
"learning_rate": 0.0001144795820237573,
|
| 259 |
+
"loss": 0.29408544540405274,
|
| 260 |
+
"step": 1500
|
| 261 |
+
},
|
| 262 |
+
{
|
| 263 |
+
"epoch": 1.443909484833895,
|
| 264 |
+
"eval_loss": 0.30712059140205383,
|
| 265 |
+
"eval_runtime": 694.8078,
|
| 266 |
+
"eval_samples_per_second": 2.658,
|
| 267 |
+
"eval_steps_per_second": 0.665,
|
| 268 |
+
"step": 1500
|
| 269 |
+
},
|
| 270 |
+
{
|
| 271 |
+
"epoch": 1.4920558497833414,
|
| 272 |
+
"grad_norm": 0.18828196823596954,
|
| 273 |
+
"learning_rate": 0.00010921441107740198,
|
| 274 |
+
"loss": 0.28817583084106446,
|
| 275 |
+
"step": 1550
|
| 276 |
+
},
|
| 277 |
+
{
|
| 278 |
+
"epoch": 1.5402022147327876,
|
| 279 |
+
"grad_norm": 0.19784030318260193,
|
| 280 |
+
"learning_rate": 0.0001039233320382344,
|
| 281 |
+
"loss": 0.292324333190918,
|
| 282 |
+
"step": 1600
|
| 283 |
+
},
|
| 284 |
+
{
|
| 285 |
+
"epoch": 1.588348579682234,
|
| 286 |
+
"grad_norm": 0.21540944278240204,
|
| 287 |
+
"learning_rate": 9.862122179482317e-05,
|
| 288 |
+
"loss": 0.2901228141784668,
|
| 289 |
+
"step": 1650
|
| 290 |
+
},
|
| 291 |
+
{
|
| 292 |
+
"epoch": 1.6364949446316803,
|
| 293 |
+
"grad_norm": 0.22679032385349274,
|
| 294 |
+
"learning_rate": 9.332298825209385e-05,
|
| 295 |
+
"loss": 0.28837751388549804,
|
| 296 |
+
"step": 1700
|
| 297 |
+
},
|
| 298 |
+
{
|
| 299 |
+
"epoch": 1.6846413095811266,
|
| 300 |
+
"grad_norm": 0.19287723302841187,
|
| 301 |
+
"learning_rate": 8.80435284148808e-05,
|
| 302 |
+
"loss": 0.28883354187011717,
|
| 303 |
+
"step": 1750
|
| 304 |
+
},
|
| 305 |
+
{
|
| 306 |
+
"epoch": 1.6846413095811266,
|
| 307 |
+
"eval_loss": 0.30308136343955994,
|
| 308 |
+
"eval_runtime": 695.3246,
|
| 309 |
+
"eval_samples_per_second": 2.656,
|
| 310 |
+
"eval_steps_per_second": 0.664,
|
| 311 |
+
"step": 1750
|
| 312 |
+
},
|
| 313 |
+
{
|
| 314 |
+
"epoch": 1.7327876745305728,
|
| 315 |
+
"grad_norm": 0.18742942810058594,
|
| 316 |
+
"learning_rate": 8.279768650212679e-05,
|
| 317 |
+
"loss": 0.2922953224182129,
|
| 318 |
+
"step": 1800
|
| 319 |
+
},
|
| 320 |
+
{
|
| 321 |
+
"epoch": 1.7809340394800193,
|
| 322 |
+
"grad_norm": 0.17063775658607483,
|
| 323 |
+
"learning_rate": 7.760021220950004e-05,
|
| 324 |
+
"loss": 0.29046398162841797,
|
| 325 |
+
"step": 1850
|
| 326 |
+
},
|
| 327 |
+
{
|
| 328 |
+
"epoch": 1.8290804044294657,
|
| 329 |
+
"grad_norm": 0.1963094025850296,
|
| 330 |
+
"learning_rate": 7.246571923778208e-05,
|
| 331 |
+
"loss": 0.28941730499267576,
|
| 332 |
+
"step": 1900
|
| 333 |
+
},
|
| 334 |
+
{
|
| 335 |
+
"epoch": 1.877226769378912,
|
| 336 |
+
"grad_norm": 0.186972513794899,
|
| 337 |
+
"learning_rate": 6.740864420363105e-05,
|
| 338 |
+
"loss": 0.28976251602172853,
|
| 339 |
+
"step": 1950
|
| 340 |
+
},
|
| 341 |
+
{
|
| 342 |
+
"epoch": 1.9253731343283582,
|
| 343 |
+
"grad_norm": 0.18225796520709991,
|
| 344 |
+
"learning_rate": 6.244320604825131e-05,
|
| 345 |
+
"loss": 0.2877297782897949,
|
| 346 |
+
"step": 2000
|
| 347 |
+
},
|
| 348 |
+
{
|
| 349 |
+
"epoch": 1.9253731343283582,
|
| 350 |
+
"eval_loss": 0.2992326021194458,
|
| 351 |
+
"eval_runtime": 695.681,
|
| 352 |
+
"eval_samples_per_second": 2.655,
|
| 353 |
+
"eval_steps_per_second": 0.664,
|
| 354 |
+
"step": 2000
|
| 355 |
+
},
|
| 356 |
+
{
|
| 357 |
+
"epoch": 1.9735194992778045,
|
| 358 |
+
"grad_norm": 0.18147684633731842,
|
| 359 |
+
"learning_rate": 5.7583366058099916e-05,
|
| 360 |
+
"loss": 0.2825794219970703,
|
| 361 |
+
"step": 2050
|
| 362 |
+
},
|
| 363 |
+
{
|
| 364 |
+
"epoch": 2.021184400577756,
|
| 365 |
+
"grad_norm": 0.21326377987861633,
|
| 366 |
+
"learning_rate": 5.284278861003815e-05,
|
| 367 |
+
"loss": 0.271549129486084,
|
| 368 |
+
"step": 2100
|
| 369 |
+
},
|
| 370 |
+
{
|
| 371 |
+
"epoch": 2.069330765527203,
|
| 372 |
+
"grad_norm": 0.2095552235841751,
|
| 373 |
+
"learning_rate": 4.823480275130263e-05,
|
| 374 |
+
"loss": 0.24787240982055664,
|
| 375 |
+
"step": 2150
|
| 376 |
+
},
|
| 377 |
+
{
|
| 378 |
+
"epoch": 2.117477130476649,
|
| 379 |
+
"grad_norm": 0.18589918315410614,
|
| 380 |
+
"learning_rate": 4.3772364722319715e-05,
|
| 381 |
+
"loss": 0.2502709770202637,
|
| 382 |
+
"step": 2200
|
| 383 |
+
},
|
| 384 |
+
{
|
| 385 |
+
"epoch": 2.1656234954260953,
|
| 386 |
+
"grad_norm": 0.2025139182806015,
|
| 387 |
+
"learning_rate": 3.946802152773811e-05,
|
| 388 |
+
"loss": 0.25036895751953125,
|
| 389 |
+
"step": 2250
|
| 390 |
+
},
|
| 391 |
+
{
|
| 392 |
+
"epoch": 2.1656234954260953,
|
| 393 |
+
"eval_loss": 0.3054317533969879,
|
| 394 |
+
"eval_runtime": 695.5773,
|
| 395 |
+
"eval_samples_per_second": 2.655,
|
| 396 |
+
"eval_steps_per_second": 0.664,
|
| 397 |
+
"step": 2250
|
| 398 |
+
},
|
| 399 |
+
{
|
| 400 |
+
"epoch": 2.2137698603755416,
|
| 401 |
+
"grad_norm": 0.23237130045890808,
|
| 402 |
+
"learning_rate": 3.533387565810706e-05,
|
| 403 |
+
"loss": 0.24967620849609376,
|
| 404 |
+
"step": 2300
|
| 405 |
+
},
|
| 406 |
+
{
|
| 407 |
+
"epoch": 2.261916225324988,
|
| 408 |
+
"grad_norm": 0.21668598055839539,
|
| 409 |
+
"learning_rate": 3.1381551061391366e-05,
|
| 410 |
+
"loss": 0.2472244071960449,
|
| 411 |
+
"step": 2350
|
| 412 |
+
},
|
| 413 |
+
{
|
| 414 |
+
"epoch": 2.310062590274434,
|
| 415 |
+
"grad_norm": 0.21904581785202026,
|
| 416 |
+
"learning_rate": 2.7622160460001166e-05,
|
| 417 |
+
"loss": 0.24260114669799804,
|
| 418 |
+
"step": 2400
|
| 419 |
+
},
|
| 420 |
+
{
|
| 421 |
+
"epoch": 2.3582089552238807,
|
| 422 |
+
"grad_norm": 0.2477143406867981,
|
| 423 |
+
"learning_rate": 2.406627410523087e-05,
|
| 424 |
+
"loss": 0.24558507919311523,
|
| 425 |
+
"step": 2450
|
| 426 |
+
},
|
| 427 |
+
{
|
| 428 |
+
"epoch": 2.406355320173327,
|
| 429 |
+
"grad_norm": 0.26366570591926575,
|
| 430 |
+
"learning_rate": 2.0723890056960227e-05,
|
| 431 |
+
"loss": 0.24778993606567382,
|
| 432 |
+
"step": 2500
|
| 433 |
+
},
|
| 434 |
+
{
|
| 435 |
+
"epoch": 2.406355320173327,
|
| 436 |
+
"eval_loss": 0.30330467224121094,
|
| 437 |
+
"eval_runtime": 695.5219,
|
| 438 |
+
"eval_samples_per_second": 2.656,
|
| 439 |
+
"eval_steps_per_second": 0.664,
|
| 440 |
+
"step": 2500
|
| 441 |
+
},
|
| 442 |
+
{
|
| 443 |
+
"epoch": 2.4545016851227732,
|
| 444 |
+
"grad_norm": 0.25673332810401917,
|
| 445 |
+
"learning_rate": 1.7604406072182122e-05,
|
| 446 |
+
"loss": 0.24701383590698242,
|
| 447 |
+
"step": 2550
|
| 448 |
+
},
|
| 449 |
+
{
|
| 450 |
+
"epoch": 2.5026480500722195,
|
| 451 |
+
"grad_norm": 0.2344675064086914,
|
| 452 |
+
"learning_rate": 1.4716593181396964e-05,
|
| 453 |
+
"loss": 0.23919960021972655,
|
| 454 |
+
"step": 2600
|
| 455 |
+
},
|
| 456 |
+
{
|
| 457 |
+
"epoch": 2.5507944150216657,
|
| 458 |
+
"grad_norm": 0.24205727875232697,
|
| 459 |
+
"learning_rate": 1.2068571027170161e-05,
|
| 460 |
+
"loss": 0.2499522399902344,
|
| 461 |
+
"step": 2650
|
| 462 |
+
},
|
| 463 |
+
{
|
| 464 |
+
"epoch": 2.5989407799711124,
|
| 465 |
+
"grad_norm": 0.18950000405311584,
|
| 466 |
+
"learning_rate": 9.667785034191811e-06,
|
| 467 |
+
"loss": 0.24822561264038087,
|
| 468 |
+
"step": 2700
|
| 469 |
+
},
|
| 470 |
+
{
|
| 471 |
+
"epoch": 2.6470871449205586,
|
| 472 |
+
"grad_norm": 0.23864181339740753,
|
| 473 |
+
"learning_rate": 7.5209854750301844e-06,
|
| 474 |
+
"loss": 0.24670083999633788,
|
| 475 |
+
"step": 2750
|
| 476 |
+
},
|
| 477 |
+
{
|
| 478 |
+
"epoch": 2.6470871449205586,
|
| 479 |
+
"eval_loss": 0.30303388833999634,
|
| 480 |
+
"eval_runtime": 696.3045,
|
| 481 |
+
"eval_samples_per_second": 2.653,
|
| 482 |
+
"eval_steps_per_second": 0.664,
|
| 483 |
+
"step": 2750
|
| 484 |
+
},
|
| 485 |
+
{
|
| 486 |
+
"epoch": 2.695233509870005,
|
| 487 |
+
"grad_norm": 0.2515101730823517,
|
| 488 |
+
"learning_rate": 5.634208490439252e-06,
|
| 489 |
+
"loss": 0.24807355880737306,
|
| 490 |
+
"step": 2800
|
| 491 |
+
},
|
| 492 |
+
{
|
| 493 |
+
"epoch": 2.743379874819451,
|
| 494 |
+
"grad_norm": 0.22556646168231964,
|
| 495 |
+
"learning_rate": 4.012759117585463e-06,
|
| 496 |
+
"loss": 0.24218505859375,
|
| 497 |
+
"step": 2850
|
| 498 |
+
},
|
| 499 |
+
{
|
| 500 |
+
"epoch": 2.7915262397688974,
|
| 501 |
+
"grad_norm": 0.21387307345867157,
|
| 502 |
+
"learning_rate": 2.661196373913288e-06,
|
| 503 |
+
"loss": 0.24130987167358398,
|
| 504 |
+
"step": 2900
|
| 505 |
+
},
|
| 506 |
+
{
|
| 507 |
+
"epoch": 2.839672604718344,
|
| 508 |
+
"grad_norm": 0.20219890773296356,
|
| 509 |
+
"learning_rate": 1.5833204385888867e-06,
|
| 510 |
+
"loss": 0.24288219451904297,
|
| 511 |
+
"step": 2950
|
| 512 |
+
},
|
| 513 |
+
{
|
| 514 |
+
"epoch": 2.88781896966779,
|
| 515 |
+
"grad_norm": 0.24099305272102356,
|
| 516 |
+
"learning_rate": 7.821619675638658e-07,
|
| 517 |
+
"loss": 0.25014289855957034,
|
| 518 |
+
"step": 3000
|
| 519 |
+
},
|
| 520 |
+
{
|
| 521 |
+
"epoch": 2.88781896966779,
|
| 522 |
+
"eval_loss": 0.3028092682361603,
|
| 523 |
+
"eval_runtime": 696.6975,
|
| 524 |
+
"eval_samples_per_second": 2.651,
|
| 525 |
+
"eval_steps_per_second": 0.663,
|
| 526 |
+
"step": 3000
|
| 527 |
+
},
|
| 528 |
+
{
|
| 529 |
+
"epoch": 2.9359653346172365,
|
| 530 |
+
"grad_norm": 0.2587520182132721,
|
| 531 |
+
"learning_rate": 2.5997357230198583e-07,
|
| 532 |
+
"loss": 0.24698244094848631,
|
| 533 |
+
"step": 3050
|
| 534 |
+
},
|
| 535 |
+
{
|
| 536 |
+
"epoch": 2.9841116995666828,
|
| 537 |
+
"grad_norm": 0.19957926869392395,
|
| 538 |
+
"learning_rate": 1.8223486127799673e-08,
|
| 539 |
+
"loss": 0.24292854309082032,
|
| 540 |
+
"step": 3100
|
| 541 |
+
}
|
| 542 |
+
],
|
| 543 |
+
"logging_steps": 50,
|
| 544 |
+
"max_steps": 3117,
|
| 545 |
+
"num_input_tokens_seen": 0,
|
| 546 |
+
"num_train_epochs": 3,
|
| 547 |
+
"save_steps": 250,
|
| 548 |
+
"stateful_callbacks": {
|
| 549 |
+
"TrainerControl": {
|
| 550 |
+
"args": {
|
| 551 |
+
"should_epoch_stop": false,
|
| 552 |
+
"should_evaluate": false,
|
| 553 |
+
"should_log": false,
|
| 554 |
+
"should_save": true,
|
| 555 |
+
"should_training_stop": true
|
| 556 |
+
},
|
| 557 |
+
"attributes": {}
|
| 558 |
+
}
|
| 559 |
+
},
|
| 560 |
+
"total_flos": 2.0828994331856486e+18,
|
| 561 |
+
"train_batch_size": 4,
|
| 562 |
+
"trial_name": null,
|
| 563 |
+
"trial_params": null
|
| 564 |
+
}
|
training_args.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:80fdf713fc6688b0d76f38e737621ec8898ba5b9aba9f862b3bac20e5ca40a2f
|
| 3 |
+
size 5713
|