File size: 3,943 Bytes
0513381 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 |
---
base_model: d0rj/rut5-base-summ
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: myspace1
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. -->
# myspace1
This model is a fine-tuned version of [d0rj/rut5-base-summ](https://huggingface.co/d0rj/rut5-base-summ) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3282
- Rouge1: 0.242
- Rouge2: 0.1107
- Rougel: 0.2373
- Rougelsum: 0.2351
- Gen Len: 55.65
## 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: 25
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log | 1.0 | 90 | 2.3719 | 0.2088 | 0.0817 | 0.2064 | 0.2072 | 39.99 |
| No log | 2.0 | 180 | 2.3539 | 0.2393 | 0.1057 | 0.2367 | 0.2363 | 42.87 |
| No log | 3.0 | 270 | 2.3378 | 0.2249 | 0.0893 | 0.2194 | 0.2187 | 46.75 |
| No log | 4.0 | 360 | 2.3271 | 0.2263 | 0.0935 | 0.2199 | 0.2195 | 49.99 |
| No log | 5.0 | 450 | 2.3220 | 0.2412 | 0.1001 | 0.2318 | 0.2328 | 53.65 |
| 1.7281 | 6.0 | 540 | 2.3206 | 0.2305 | 0.0978 | 0.2238 | 0.223 | 55.28 |
| 1.7281 | 7.0 | 630 | 2.3194 | 0.2338 | 0.1044 | 0.2276 | 0.2274 | 55.01 |
| 1.7281 | 8.0 | 720 | 2.3197 | 0.2449 | 0.1085 | 0.2383 | 0.237 | 55.42 |
| 1.7281 | 9.0 | 810 | 2.3201 | 0.2526 | 0.1114 | 0.2481 | 0.2455 | 56.34 |
| 1.7281 | 10.0 | 900 | 2.3204 | 0.238 | 0.103 | 0.2331 | 0.2302 | 55.9 |
| 1.7281 | 11.0 | 990 | 2.3214 | 0.2372 | 0.1133 | 0.2334 | 0.231 | 55.46 |
| 1.4551 | 12.0 | 1080 | 2.3220 | 0.2418 | 0.1158 | 0.2361 | 0.2352 | 56.44 |
| 1.4551 | 13.0 | 1170 | 2.3229 | 0.25 | 0.1209 | 0.2454 | 0.2433 | 55.8 |
| 1.4551 | 14.0 | 1260 | 2.3240 | 0.2507 | 0.124 | 0.2465 | 0.2448 | 55.09 |
| 1.4551 | 15.0 | 1350 | 2.3247 | 0.2561 | 0.1247 | 0.2505 | 0.2491 | 54.39 |
| 1.4551 | 16.0 | 1440 | 2.3256 | 0.2452 | 0.1198 | 0.2396 | 0.2379 | 53.75 |
| 1.3726 | 17.0 | 1530 | 2.3258 | 0.2367 | 0.1137 | 0.2305 | 0.2285 | 54.84 |
| 1.3726 | 18.0 | 1620 | 2.3265 | 0.2403 | 0.1159 | 0.2349 | 0.2329 | 54.56 |
| 1.3726 | 19.0 | 1710 | 2.3264 | 0.2381 | 0.1132 | 0.2335 | 0.2303 | 55.01 |
| 1.3726 | 20.0 | 1800 | 2.3270 | 0.2418 | 0.1133 | 0.2371 | 0.2346 | 55.21 |
| 1.3726 | 21.0 | 1890 | 2.3273 | 0.2413 | 0.1133 | 0.2368 | 0.234 | 55.84 |
| 1.3726 | 22.0 | 1980 | 2.3275 | 0.2431 | 0.1137 | 0.2388 | 0.2367 | 55.82 |
| 1.3286 | 23.0 | 2070 | 2.3277 | 0.2424 | 0.1106 | 0.2376 | 0.2354 | 56.05 |
| 1.3286 | 24.0 | 2160 | 2.3280 | 0.242 | 0.1107 | 0.2373 | 0.2351 | 55.87 |
| 1.3286 | 25.0 | 2250 | 2.3282 | 0.242 | 0.1107 | 0.2373 | 0.2351 | 55.65 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0
|