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# qa_bm25_small_sample2

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 4.1438
- Rouge1: 0.1048
- Rouge2: 0.0088
- Rougel: 0.0949
- Rougelsum: 0.0949
- Gen Len: 19.0

## 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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 108  | 12.1686         | 0.014  | 0.0    | 0.0134 | 0.0132    | 6.0357  |
| No log        | 2.0   | 216  | 10.8608         | 0.0122 | 0.0    | 0.0113 | 0.0113    | 6.0     |
| No log        | 3.0   | 324  | 8.0196          | 0.044  | 0.008  | 0.041  | 0.0407    | 9.1429  |
| No log        | 4.0   | 432  | 5.8188          | 0.1099 | 0.0119 | 0.0988 | 0.0983    | 19.0    |
| 13.9065       | 5.0   | 540  | 4.6813          | 0.1254 | 0.0138 | 0.1104 | 0.1103    | 19.0    |
| 13.9065       | 6.0   | 648  | 4.3367          | 0.1229 | 0.0158 | 0.1094 | 0.1097    | 19.0    |
| 13.9065       | 7.0   | 756  | 4.2485          | 0.1172 | 0.0145 | 0.1033 | 0.1037    | 19.0    |
| 13.9065       | 8.0   | 864  | 4.1780          | 0.1048 | 0.0088 | 0.0949 | 0.0949    | 19.0    |
| 13.9065       | 9.0   | 972  | 4.1546          | 0.1048 | 0.0088 | 0.0949 | 0.0949    | 19.0    |
| 6.0382        | 10.0  | 1080 | 4.1438          | 0.1048 | 0.0088 | 0.0949 | 0.0949    | 19.0    |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "qa_bm25_small_sample2", "results": []}]}
transformers pytorch tensorboard mt5 text2text-generation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #mt5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

qa\_bm25\_small\_sample2
========================


This model is a fine-tuned version of google/mt5-small on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 4.1438
* Rouge1: 0.1048
* Rouge2: 0.0088
* Rougel: 0.0949
* Rougelsum: 0.0949
* Gen Len: 19.0


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: 1
* eval\_batch\_size: 1
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #mt5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 1
* eval\_batch\_size: 1
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.28.0
* Pytorch 2.0.1+cu118
* Datasets 2.12.0
* Tokenizers 0.13.3