Model Overview

This model, laion/exp-uns-r2egym-2_1x_glm_4_7_traces_locetash, is an 8 billion parameter language model derived from the Qwen3-8B architecture. It has been fine-tuned specifically on the DCAgent/exp-uns-r2egym-2_1x_glm_4.7_traces_locetash dataset, indicating a potential specialization in tasks or domains represented by this particular dataset. The model supports a substantial context length of 32768 tokens, allowing it to process and generate longer sequences of text.

Training Details

The fine-tuning process involved several key hyperparameters:

• Learning Rate: 4e-05
• Optimizer: ADAMW_TORCH_FUSED with betas=(0.9, 0.98) and epsilon=1e-08
• Epochs: 7.0
• Batch Size: A total training batch size of 16 (with gradient accumulation steps of 2 and a train_batch_size of 1 per device) was used across 8 GPUs.
• LR Scheduler: Cosine scheduler with a warmup ratio of 0.1.

Intended Use Cases

Given its fine-tuning on a specific dataset, this model is likely best suited for applications that align with the characteristics and content of the DCAgent/exp-uns-r2egym-2_1x_glm_4.7_traces_locetash dataset. Developers should evaluate its performance on tasks related to this domain to determine its suitability.