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# repro_cnn_dailymail

This model is a fine-tuned version of [Qwen/Qwen-14B](https://huggingface.co/Qwen/Qwen-14B) on the cnn_dailymail dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8993

## 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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 0.01
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.9738        | 0.02  | 50   | 1.9729          |
| 1.9702        | 0.04  | 100  | 1.9553          |
| 1.9476        | 0.06  | 150  | 1.9318          |
| 1.9205        | 0.08  | 200  | 1.9123          |
| 1.9022        | 0.1   | 250  | 1.9005          |
| 1.886         | 0.12  | 300  | 1.8939          |
| 1.8872        | 0.14  | 350  | 1.8898          |
| 1.8704        | 0.16  | 400  | 1.8894          |
| 1.894         | 0.18  | 450  | 1.8901          |
| 1.8965        | 0.2   | 500  | 1.8911          |
| 1.8899        | 0.22  | 550  | 1.8908          |
| 1.8962        | 0.24  | 600  | 1.8916          |
| 1.8781        | 0.26  | 650  | 1.8911          |
| 1.8848        | 0.28  | 700  | 1.8908          |
| 1.8785        | 0.3   | 750  | 1.8902          |
| 1.8787        | 0.32  | 800  | 1.8910          |
| 1.9216        | 0.34  | 850  | 1.8914          |
| 1.8984        | 0.36  | 900  | 1.8913          |
| 1.8931        | 0.38  | 950  | 1.8911          |
| 1.878         | 0.4   | 1000 | 1.8912          |
| 1.8904        | 0.42  | 1050 | 1.8922          |
| 1.8826        | 0.44  | 1100 | 1.8924          |
| 1.8864        | 0.46  | 1150 | 1.8927          |
| 1.886         | 0.48  | 1200 | 1.8929          |
| 1.8955        | 0.5   | 1250 | 1.8935          |
| 1.8888        | 0.52  | 1300 | 1.8942          |
| 1.8948        | 0.54  | 1350 | 1.8947          |
| 1.8907        | 0.56  | 1400 | 1.8950          |
| 1.8869        | 0.58  | 1450 | 1.8952          |
| 1.8939        | 0.6   | 1500 | 1.8958          |
| 1.8866        | 0.62  | 1550 | 1.8967          |
| 1.8892        | 0.64  | 1600 | 1.8968          |
| 1.8947        | 0.66  | 1650 | 1.8969          |
| 1.885         | 0.68  | 1700 | 1.8976          |
| 1.8775        | 0.7   | 1750 | 1.8977          |
| 1.914         | 0.72  | 1800 | 1.8982          |
| 1.8958        | 0.74  | 1850 | 1.8984          |
| 1.8886        | 0.76  | 1900 | 1.8984          |
| 1.9034        | 0.78  | 1950 | 1.8988          |
| 1.8818        | 0.8   | 2000 | 1.8988          |
| 1.8986        | 0.82  | 2050 | 1.8988          |
| 1.8889        | 0.84  | 2100 | 1.8989          |
| 1.8981        | 0.86  | 2150 | 1.8991          |
| 1.9003        | 0.88  | 2200 | 1.8992          |
| 1.8966        | 0.9   | 2250 | 1.8993          |
| 1.8921        | 0.92  | 2300 | 1.8992          |
| 1.8786        | 0.94  | 2350 | 1.8993          |
| 1.8955        | 0.96  | 2400 | 1.8993          |
| 1.9164        | 0.98  | 2450 | 1.8993          |
| 1.8898        | 1.0   | 2500 | 1.8993          |


### Framework versions

- Transformers 4.32.0
- Pytorch 2.1.0
- Datasets 2.15.0
- Tokenizers 0.13.3

{"tags": ["generated_from_trainer"], "datasets": ["cnn_dailymail"], "base_model": "Qwen/Qwen-14B", "model-index": [{"name": "repro_cnn_dailymail", "results": []}]}
generated_from_trainer dataset:cnn_dailymail base_model:Qwen/Qwen-14B region:us