lpetreadg/trained-tinyllama-ultrachat-GGUF
Quantized GGUF model files for trained-tinyllama-ultrachat from lpetreadg
| Name | Quant method | Size |
|---|---|---|
| trained-tinyllama-ultrachat.q2_k.gguf | q2_k | None |
| trained-tinyllama-ultrachat.q3_k_m.gguf | q3_k_m | None |
| trained-tinyllama-ultrachat.q4_k_m.gguf | q4_k_m | None |
| trained-tinyllama-ultrachat.q5_k_m.gguf | q5_k_m | None |
| trained-tinyllama-ultrachat.q6_k.gguf | q6_k | None |
| trained-tinyllama-ultrachat.q8_0.gguf | q8_0 | None |
Original Model Card:
trained-tinyllama-ultrachat
This model is a fine-tuned version of PY007/TinyLlama-1.1B-intermediate-step-715k-1.5T on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.3258
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.3767 | 0.08 | 100 | 1.3685 |
| 1.3494 | 0.17 | 200 | 1.3490 |
| 1.3436 | 0.25 | 300 | 1.3389 |
| 1.3231 | 0.33 | 400 | 1.3331 |
| 1.3278 | 0.42 | 500 | 1.3296 |
| 1.3214 | 0.5 | 600 | 1.3276 |
| 1.3376 | 0.58 | 700 | 1.3266 |
| 1.3227 | 0.67 | 800 | 1.3261 |
| 1.3329 | 0.75 | 900 | 1.3259 |
| 1.3185 | 0.83 | 1000 | 1.3258 |
| 1.332 | 0.92 | 1100 | 1.3258 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1