Instructions to use FatCat87/taopanda-3_c71cc5c5-b4a1-43b5-93ac-4f9fe77ee451 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use FatCat87/taopanda-3_c71cc5c5-b4a1-43b5-93ac-4f9fe77ee451 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2-0.5B") model = PeftModel.from_pretrained(base_model, "FatCat87/taopanda-3_c71cc5c5-b4a1-43b5-93ac-4f9fe77ee451") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files- README.md +6 -6
- adapter_model.bin +1 -1
README.md
CHANGED
|
@@ -71,7 +71,7 @@ pad_to_sequence_len: true
|
|
| 71 |
resume_from_checkpoint: null
|
| 72 |
sample_packing: true
|
| 73 |
saves_per_epoch: 1
|
| 74 |
-
seed:
|
| 75 |
sequence_len: 4096
|
| 76 |
special_tokens: null
|
| 77 |
strict: false
|
|
@@ -95,12 +95,12 @@ xformers_attention: null
|
|
| 95 |
|
| 96 |
</details><br>
|
| 97 |
|
| 98 |
-
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/fatcat87-taopanda/subnet56/runs/
|
| 99 |
# taopanda-3_c71cc5c5-b4a1-43b5-93ac-4f9fe77ee451
|
| 100 |
|
| 101 |
This model is a fine-tuned version of [unsloth/Qwen2-0.5B](https://huggingface.co/unsloth/Qwen2-0.5B) on the None dataset.
|
| 102 |
It achieves the following results on the evaluation set:
|
| 103 |
-
- Loss: 1.
|
| 104 |
|
| 105 |
## Model description
|
| 106 |
|
|
@@ -122,7 +122,7 @@ The following hyperparameters were used during training:
|
|
| 122 |
- learning_rate: 0.0002
|
| 123 |
- train_batch_size: 2
|
| 124 |
- eval_batch_size: 2
|
| 125 |
-
- seed:
|
| 126 |
- distributed_type: multi-GPU
|
| 127 |
- num_devices: 4
|
| 128 |
- gradient_accumulation_steps: 4
|
|
@@ -136,8 +136,8 @@ The following hyperparameters were used during training:
|
|
| 136 |
|
| 137 |
| Training Loss | Epoch | Step | Validation Loss |
|
| 138 |
|:-------------:|:------:|:----:|:---------------:|
|
| 139 |
-
| 1.
|
| 140 |
-
| 0.
|
| 141 |
|
| 142 |
|
| 143 |
### Framework versions
|
|
|
|
| 71 |
resume_from_checkpoint: null
|
| 72 |
sample_packing: true
|
| 73 |
saves_per_epoch: 1
|
| 74 |
+
seed: 58426
|
| 75 |
sequence_len: 4096
|
| 76 |
special_tokens: null
|
| 77 |
strict: false
|
|
|
|
| 95 |
|
| 96 |
</details><br>
|
| 97 |
|
| 98 |
+
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/fatcat87-taopanda/subnet56/runs/zpzfcink)
|
| 99 |
# taopanda-3_c71cc5c5-b4a1-43b5-93ac-4f9fe77ee451
|
| 100 |
|
| 101 |
This model is a fine-tuned version of [unsloth/Qwen2-0.5B](https://huggingface.co/unsloth/Qwen2-0.5B) on the None dataset.
|
| 102 |
It achieves the following results on the evaluation set:
|
| 103 |
+
- Loss: 1.8121
|
| 104 |
|
| 105 |
## Model description
|
| 106 |
|
|
|
|
| 122 |
- learning_rate: 0.0002
|
| 123 |
- train_batch_size: 2
|
| 124 |
- eval_batch_size: 2
|
| 125 |
+
- seed: 58426
|
| 126 |
- distributed_type: multi-GPU
|
| 127 |
- num_devices: 4
|
| 128 |
- gradient_accumulation_steps: 4
|
|
|
|
| 136 |
|
| 137 |
| Training Loss | Epoch | Step | Validation Loss |
|
| 138 |
|:-------------:|:------:|:----:|:---------------:|
|
| 139 |
+
| 1.4385 | 1.0 | 1 | 1.9115 |
|
| 140 |
+
| 0.4521 | 1.3333 | 2 | 1.8121 |
|
| 141 |
|
| 142 |
|
| 143 |
### Framework versions
|
adapter_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 70506570
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:ed4e88c24615c980519e73fb26b06c300d60627f2f9060fb5dfce610c4eb4284
|
| 3 |
size 70506570
|