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---
license: apache-2.0
base_model: allenai/led-base-16384
tags:
- generated_from_trainer
model-index:
- name: hf
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# hf
This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2202
## 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: 3e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: polynomial
- lr_scheduler_warmup_steps: 500
- training_steps: 20000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.255 | 0.0 | 500 | 0.2798 |
| 0.211 | 0.01 | 1000 | 0.2655 |
| 0.2399 | 0.01 | 1500 | 0.2625 |
| 0.2183 | 0.01 | 2000 | 0.2533 |
| 0.2375 | 0.02 | 2500 | 0.2501 |
| 0.2452 | 0.02 | 3000 | 0.2477 |
| 0.2636 | 0.02 | 3500 | 0.2474 |
| 0.2289 | 0.03 | 4000 | 0.2476 |
| 0.2453 | 0.03 | 4500 | 0.2443 |
| 0.2081 | 0.03 | 5000 | 0.2441 |
| 0.1655 | 0.04 | 5500 | 0.2422 |
| 0.2765 | 0.04 | 6000 | 0.2386 |
| 0.2797 | 0.05 | 6500 | 0.2398 |
| 0.1902 | 0.05 | 7000 | 0.2393 |
| 0.1875 | 0.05 | 7500 | 0.2363 |
| 0.2048 | 0.06 | 8000 | 0.2371 |
| 0.1695 | 0.06 | 8500 | 0.2341 |
| 0.2121 | 0.06 | 9000 | 0.2348 |
| 0.2402 | 0.07 | 9500 | 0.2331 |
| 0.1865 | 0.07 | 10000 | 0.2324 |
| 0.1862 | 0.07 | 10500 | 0.2329 |
| 0.2382 | 0.08 | 11000 | 0.2323 |
| 0.2703 | 0.08 | 11500 | 0.2300 |
| 0.2303 | 0.08 | 12000 | 0.2297 |
| 0.2258 | 0.09 | 12500 | 0.2287 |
| 0.1924 | 0.09 | 13000 | 0.2271 |
| 0.1849 | 0.09 | 13500 | 0.2269 |
| 0.2288 | 0.1 | 14000 | 0.2257 |
| 0.2461 | 0.1 | 14500 | 0.2259 |
| 0.2509 | 0.1 | 15000 | 0.2241 |
| 0.2087 | 0.11 | 15500 | 0.2245 |
| 0.1707 | 0.11 | 16000 | 0.2243 |
| 0.2053 | 0.11 | 16500 | 0.2238 |
| 0.2157 | 0.12 | 17000 | 0.2225 |
| 0.1976 | 0.12 | 17500 | 0.2218 |
| 0.2626 | 0.13 | 18000 | 0.2213 |
| 0.2032 | 0.13 | 18500 | 0.2209 |
| 0.2928 | 0.13 | 19000 | 0.2207 |
| 0.2438 | 0.14 | 19500 | 0.2205 |
| 0.2028 | 0.14 | 20000 | 0.2202 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.1
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