---
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