nthakur/miracl-crosslingual-sft-x-en
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How to use nthakur/Meta-Llama-3-8B-Instruct-miracl-mix-raft-sft-25th-apr-v1.0 with PEFT:
from peft import PeftModel
from transformers import AutoModelForCausalLM
base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3-8B-Instruct")
model = PeftModel.from_pretrained(base_model, "nthakur/Meta-Llama-3-8B-Instruct-miracl-mix-raft-sft-25th-apr-v1.0")This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on the nthakur/miracl-raft-sft-instruct-v0.1, the nthakur/nomiracl-raft-sft-instruct-v0.1, the nthakur/miracl-en-x-raft-sft-instruct-v0.1 and the nthakur/miracl-x-en-raft-sft-instruct-v0.1 datasets. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.4903 | 0.09 | 200 | 1.3961 |
| 1.465 | 0.18 | 400 | 1.3499 |
| 1.4193 | 0.28 | 600 | 1.3330 |
| 1.3593 | 0.37 | 800 | 1.3232 |
| 1.3552 | 0.46 | 1000 | 1.3166 |
| 1.3685 | 0.55 | 1200 | 1.3123 |
| 1.3487 | 0.64 | 1400 | 1.3094 |
| 1.3891 | 0.74 | 1600 | 1.3076 |
| 1.3858 | 0.83 | 1800 | 1.3067 |
| 1.3635 | 0.92 | 2000 | 1.3064 |
Base model
meta-llama/Meta-Llama-3-8B-Instruct