CapyLake-7B-v2-laser
This model is a finetune of cognitivecomputations/WestLake-7B-v2-Laser on argilla/distilabel-capybara-dpo-7k-binarized
Process
- Realigned the chat template to ChatML
- Completed 1 Epoch
- 5e-05 learning rate
- Training time was about 2 hours on 1 H100
- Cost was ~$8
Code Example
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "macadeliccc/CapyLake-7B-v2-laser"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)
text = "Create an idea for a TV show and write a short pilot script"
inputs = tokenizer(text, return_tensors="pt")
# Adding hyperparameters to the generation call
outputs = model.generate(
**inputs,
max_new_tokens=4096, # Controls the maximum length of the new tokens created
temperature=0.7, # Adjust for creativity (lower is less random)
top_k=50, # Keeps the top k tokens for sampling
top_p=0.95, # Uses nucleus sampling with this cumulative probability
num_return_sequences=1, # Number of sequences to generate
no_repeat_ngram_size=2, # Prevents repeating n-grams to ensure diversity
early_stopping=True # Stops generation when all sequences reach the EOS token
)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
Other Capy Models
SOLAR-10.7B-Capy-v1.0 is also on the way. There could be more depending on performance!
Evaluations
Model | AGIEval | GPT4All | TruthfulQA | Bigbench | Average |
---|---|---|---|---|---|
CapyLake-7B-v2-laser | 44.34 | 77.77 | 68.47 | 47.92 | 59.62 |
AGIEval
Task | Version | Metric | Value | Stderr | |
---|---|---|---|---|---|
agieval_aqua_rat | 0 | acc | 28.35 | ± | 2.83 |
acc_norm | 25.98 | ± | 2.76 | ||
agieval_logiqa_en | 0 | acc | 38.86 | ± | 1.91 |
acc_norm | 39.02 | ± | 1.91 | ||
agieval_lsat_ar | 0 | acc | 25.22 | ± | 2.87 |
acc_norm | 24.35 | ± | 2.84 | ||
agieval_lsat_lr | 0 | acc | 50.39 | ± | 2.22 |
acc_norm | 51.57 | ± | 2.22 | ||
agieval_lsat_rc | 0 | acc | 65.06 | ± | 2.91 |
acc_norm | 63.94 | ± | 2.93 | ||
agieval_sat_en | 0 | acc | 78.64 | ± | 2.86 |
acc_norm | 78.64 | ± | 2.86 | ||
agieval_sat_en_without_passage | 0 | acc | 40.78 | ± | 3.43 |
acc_norm | 40.78 | ± | 3.43 | ||
agieval_sat_math | 0 | acc | 33.64 | ± | 3.19 |
acc_norm | 30.45 | ± | 3.11 |
Average: 44.34%
GPT4All
Task | Version | Metric | Value | Stderr | |
---|---|---|---|---|---|
arc_challenge | 0 | acc | 66.89 | ± | 1.38 |
acc_norm | 67.49 | ± | 1.37 | ||
arc_easy | 0 | acc | 86.70 | ± | 0.70 |
acc_norm | 81.90 | ± | 0.79 | ||
boolq | 1 | acc | 88.10 | ± | 0.57 |
hellaswag | 0 | acc | 71.45 | ± | 0.45 |
acc_norm | 87.78 | ± | 0.33 | ||
openbookqa | 0 | acc | 39.80 | ± | 2.19 |
acc_norm | 49.80 | ± | 2.24 | ||
piqa | 0 | acc | 82.86 | ± | 0.88 |
acc_norm | 84.87 | ± | 0.84 | ||
winogrande | 0 | acc | 84.45 | ± | 1.02 |
Average: 77.77%
TruthfulQA
Task | Version | Metric | Value | Stderr | |
---|---|---|---|---|---|
truthfulqa_mc | 1 | mc1 | 53.98 | ± | 1.74 |
mc2 | 68.47 | ± | 1.53 |
Average: 68.47%
Bigbench
Task | Version | Metric | Value | Stderr | |
---|---|---|---|---|---|
bigbench_causal_judgement | 0 | multiple_choice_grade | 59.47 | ± | 3.57 |
bigbench_date_understanding | 0 | multiple_choice_grade | 64.50 | ± | 2.49 |
bigbench_disambiguation_qa | 0 | multiple_choice_grade | 44.96 | ± | 3.10 |
bigbench_geometric_shapes | 0 | multiple_choice_grade | 22.84 | ± | 2.22 |
exact_str_match | 2.79 | ± | 0.87 | ||
bigbench_logical_deduction_five_objects | 0 | multiple_choice_grade | 30.80 | ± | 2.07 |
bigbench_logical_deduction_seven_objects | 0 | multiple_choice_grade | 21.57 | ± | 1.56 |
bigbench_logical_deduction_three_objects | 0 | multiple_choice_grade | 56.67 | ± | 2.87 |
bigbench_movie_recommendation | 0 | multiple_choice_grade | 51.60 | ± | 2.24 |
bigbench_navigate | 0 | multiple_choice_grade | 51.00 | ± | 1.58 |
bigbench_reasoning_about_colored_objects | 0 | multiple_choice_grade | 70.35 | ± | 1.02 |
bigbench_ruin_names | 0 | multiple_choice_grade | 51.79 | ± | 2.36 |
bigbench_salient_translation_error_detection | 0 | multiple_choice_grade | 35.97 | ± | 1.52 |
bigbench_snarks | 0 | multiple_choice_grade | 79.01 | ± | 3.04 |
bigbench_sports_understanding | 0 | multiple_choice_grade | 75.66 | ± | 1.37 |
bigbench_temporal_sequences | 0 | multiple_choice_grade | 47.90 | ± | 1.58 |
bigbench_tracking_shuffled_objects_five_objects | 0 | multiple_choice_grade | 23.84 | ± | 1.21 |
bigbench_tracking_shuffled_objects_seven_objects | 0 | multiple_choice_grade | 18.00 | ± | 0.92 |
bigbench_tracking_shuffled_objects_three_objects | 0 | multiple_choice_grade | 56.67 | ± | 2.87 |
Average: 47.92%
Average score: 59.62%
Elapsed time: 01:57:56
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