Farouk commited on
Commit
9a73bfb
·
1 Parent(s): cb0e5ee

Training in progress, step 7800

Browse files
adapter_model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:f38f5955c9bf9c9962e4bb38939ff80c61efe8c0b7444d38394083b00d53aede
3
  size 319977229
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0df8f6c3a03ff1e980781728929a4e5980bd07a23eadecc4b988c5a5a17dd290
3
  size 319977229
checkpoint-7000/adapter_model/adapter_model/README.md CHANGED
@@ -26,6 +26,17 @@ The following `bitsandbytes` quantization config was used during training:
26
  - bnb_4bit_use_double_quant: True
27
  - bnb_4bit_compute_dtype: bfloat16
28
 
 
 
 
 
 
 
 
 
 
 
 
29
  The following `bitsandbytes` quantization config was used during training:
30
  - load_in_8bit: False
31
  - load_in_4bit: True
@@ -38,6 +49,7 @@ The following `bitsandbytes` quantization config was used during training:
38
  - bnb_4bit_compute_dtype: bfloat16
39
  ### Framework versions
40
 
 
41
  - PEFT 0.4.0
42
  - PEFT 0.4.0
43
 
 
26
  - bnb_4bit_use_double_quant: True
27
  - bnb_4bit_compute_dtype: bfloat16
28
 
29
+ The following `bitsandbytes` quantization config was used during training:
30
+ - load_in_8bit: False
31
+ - load_in_4bit: True
32
+ - llm_int8_threshold: 6.0
33
+ - llm_int8_skip_modules: None
34
+ - llm_int8_enable_fp32_cpu_offload: False
35
+ - llm_int8_has_fp16_weight: False
36
+ - bnb_4bit_quant_type: nf4
37
+ - bnb_4bit_use_double_quant: True
38
+ - bnb_4bit_compute_dtype: bfloat16
39
+
40
  The following `bitsandbytes` quantization config was used during training:
41
  - load_in_8bit: False
42
  - load_in_4bit: True
 
49
  - bnb_4bit_compute_dtype: bfloat16
50
  ### Framework versions
51
 
52
+ - PEFT 0.4.0
53
  - PEFT 0.4.0
54
  - PEFT 0.4.0
55
 
checkpoint-7000/adapter_model/adapter_model/adapter_model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:afcf03f0355c751249f8d62b962579dd9de9885e57fe2ad00cead2d24bf1e481
3
  size 319977229
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f38f5955c9bf9c9962e4bb38939ff80c61efe8c0b7444d38394083b00d53aede
3
  size 319977229
{checkpoint-5600 → checkpoint-7800}/README.md RENAMED
File without changes
{checkpoint-5600 → checkpoint-7800}/adapter_config.json RENAMED
File without changes
{checkpoint-5600 → checkpoint-7800}/adapter_model.bin RENAMED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:0a9672baa899f841f65bf579e86230fb9f50bbd7d6f93db63ff4625e9a20f380
3
  size 319977229
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0df8f6c3a03ff1e980781728929a4e5980bd07a23eadecc4b988c5a5a17dd290
3
  size 319977229
{checkpoint-5600 → checkpoint-7800}/added_tokens.json RENAMED
File without changes
{checkpoint-5600 → checkpoint-7800}/optimizer.pt RENAMED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:b8ed3954cc41440e043f63ad61966691af7849dc8a88610a7c2f4f2a1e7baa5f
3
  size 1279539973
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9cfe4933ead5f20e8857f63d7c1e0a25ac8d8a28529baf16dfa4ad8ec473fd97
3
  size 1279539973
{checkpoint-5600 → checkpoint-7800}/rng_state.pth RENAMED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:b0e8b53bfb70c42ce5aa70751fa383c10aa05b5e15187d5a04669b0984631751
3
  size 14511
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6676d5462d5bf13e292f296628434f29a91a6679806fbac644617d512220e022
3
  size 14511
{checkpoint-5600 → checkpoint-7800}/scheduler.pt RENAMED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:ba9e18c7c96a1432f6ee82e99802fc56a2dd7ef9d1f20dda433c9b754ac0514c
3
  size 627
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:1dacf398b0d6d2240140ad9378ba550412b1b83c6451eaa8a75d5f42da197d1c
3
  size 627
{checkpoint-5600 → checkpoint-7800}/special_tokens_map.json RENAMED
File without changes
{checkpoint-5600 → checkpoint-7800}/tokenizer.model RENAMED
File without changes
{checkpoint-5600 → checkpoint-7800}/tokenizer_config.json RENAMED
File without changes
{checkpoint-5600 → checkpoint-7800}/trainer_state.json RENAMED
@@ -1,8 +1,8 @@
1
  {
2
- "best_metric": 0.6623189449310303,
3
- "best_model_checkpoint": "experts/expert-29/checkpoint-3800",
4
- "epoch": 1.4139628834743088,
5
- "global_step": 5600,
6
  "is_hyper_param_search": false,
7
  "is_local_process_zero": true,
8
  "is_world_process_zero": true,
@@ -5354,11 +5354,2112 @@
5354
  "mmlu_eval_accuracy_world_religions": 0.631578947368421,
5355
  "mmlu_loss": 1.3557121806605366,
5356
  "step": 5600
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
5357
  }
5358
  ],
5359
  "max_steps": 10000,
5360
  "num_train_epochs": 3,
5361
- "total_flos": 3.3216850095130214e+17,
5362
  "trial_name": null,
5363
  "trial_params": null
5364
  }
 
1
  {
2
+ "best_metric": 0.654138445854187,
3
+ "best_model_checkpoint": "experts/expert-29/checkpoint-7800",
4
+ "epoch": 1.969448301982073,
5
+ "global_step": 7800,
6
  "is_hyper_param_search": false,
7
  "is_local_process_zero": true,
8
  "is_world_process_zero": true,
 
5354
  "mmlu_eval_accuracy_world_religions": 0.631578947368421,
5355
  "mmlu_loss": 1.3557121806605366,
5356
  "step": 5600
5357
+ },
5358
+ {
5359
+ "epoch": 1.42,
5360
+ "learning_rate": 0.0002,
5361
+ "loss": 0.6009,
5362
+ "step": 5610
5363
+ },
5364
+ {
5365
+ "epoch": 1.42,
5366
+ "learning_rate": 0.0002,
5367
+ "loss": 0.5869,
5368
+ "step": 5620
5369
+ },
5370
+ {
5371
+ "epoch": 1.42,
5372
+ "learning_rate": 0.0002,
5373
+ "loss": 0.6257,
5374
+ "step": 5630
5375
+ },
5376
+ {
5377
+ "epoch": 1.42,
5378
+ "learning_rate": 0.0002,
5379
+ "loss": 0.6091,
5380
+ "step": 5640
5381
+ },
5382
+ {
5383
+ "epoch": 1.43,
5384
+ "learning_rate": 0.0002,
5385
+ "loss": 0.628,
5386
+ "step": 5650
5387
+ },
5388
+ {
5389
+ "epoch": 1.43,
5390
+ "learning_rate": 0.0002,
5391
+ "loss": 0.6313,
5392
+ "step": 5660
5393
+ },
5394
+ {
5395
+ "epoch": 1.43,
5396
+ "learning_rate": 0.0002,
5397
+ "loss": 0.597,
5398
+ "step": 5670
5399
+ },
5400
+ {
5401
+ "epoch": 1.43,
5402
+ "learning_rate": 0.0002,
5403
+ "loss": 0.5846,
5404
+ "step": 5680
5405
+ },
5406
+ {
5407
+ "epoch": 1.44,
5408
+ "learning_rate": 0.0002,
5409
+ "loss": 0.622,
5410
+ "step": 5690
5411
+ },
5412
+ {
5413
+ "epoch": 1.44,
5414
+ "learning_rate": 0.0002,
5415
+ "loss": 0.6059,
5416
+ "step": 5700
5417
+ },
5418
+ {
5419
+ "epoch": 1.44,
5420
+ "learning_rate": 0.0002,
5421
+ "loss": 0.6418,
5422
+ "step": 5710
5423
+ },
5424
+ {
5425
+ "epoch": 1.44,
5426
+ "learning_rate": 0.0002,
5427
+ "loss": 0.5709,
5428
+ "step": 5720
5429
+ },
5430
+ {
5431
+ "epoch": 1.45,
5432
+ "learning_rate": 0.0002,
5433
+ "loss": 0.6216,
5434
+ "step": 5730
5435
+ },
5436
+ {
5437
+ "epoch": 1.45,
5438
+ "learning_rate": 0.0002,
5439
+ "loss": 0.6505,
5440
+ "step": 5740
5441
+ },
5442
+ {
5443
+ "epoch": 1.45,
5444
+ "learning_rate": 0.0002,
5445
+ "loss": 0.6314,
5446
+ "step": 5750
5447
+ },
5448
+ {
5449
+ "epoch": 1.45,
5450
+ "learning_rate": 0.0002,
5451
+ "loss": 0.6256,
5452
+ "step": 5760
5453
+ },
5454
+ {
5455
+ "epoch": 1.46,
5456
+ "learning_rate": 0.0002,
5457
+ "loss": 0.6181,
5458
+ "step": 5770
5459
+ },
5460
+ {
5461
+ "epoch": 1.46,
5462
+ "learning_rate": 0.0002,
5463
+ "loss": 0.5433,
5464
+ "step": 5780
5465
+ },
5466
+ {
5467
+ "epoch": 1.46,
5468
+ "learning_rate": 0.0002,
5469
+ "loss": 0.6229,
5470
+ "step": 5790
5471
+ },
5472
+ {
5473
+ "epoch": 1.46,
5474
+ "learning_rate": 0.0002,
5475
+ "loss": 0.6269,
5476
+ "step": 5800
5477
+ },
5478
+ {
5479
+ "epoch": 1.46,
5480
+ "eval_loss": 0.6600909233093262,
5481
+ "eval_runtime": 90.1949,
5482
+ "eval_samples_per_second": 11.087,
5483
+ "eval_steps_per_second": 5.544,
5484
+ "step": 5800
5485
+ },
5486
+ {
5487
+ "epoch": 1.46,
5488
+ "mmlu_eval_accuracy": 0.4750359595194246,
5489
+ "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
5490
+ "mmlu_eval_accuracy_anatomy": 0.5714285714285714,
5491
+ "mmlu_eval_accuracy_astronomy": 0.5,
5492
+ "mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
5493
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5862068965517241,
5494
+ "mmlu_eval_accuracy_college_biology": 0.3125,
5495
+ "mmlu_eval_accuracy_college_chemistry": 0.25,
5496
+ "mmlu_eval_accuracy_college_computer_science": 0.36363636363636365,
5497
+ "mmlu_eval_accuracy_college_mathematics": 0.36363636363636365,
5498
+ "mmlu_eval_accuracy_college_medicine": 0.6363636363636364,
5499
+ "mmlu_eval_accuracy_college_physics": 0.36363636363636365,
5500
+ "mmlu_eval_accuracy_computer_security": 0.36363636363636365,
5501
+ "mmlu_eval_accuracy_conceptual_physics": 0.38461538461538464,
5502
+ "mmlu_eval_accuracy_econometrics": 0.25,
5503
+ "mmlu_eval_accuracy_electrical_engineering": 0.3125,
5504
+ "mmlu_eval_accuracy_elementary_mathematics": 0.3170731707317073,
5505
+ "mmlu_eval_accuracy_formal_logic": 0.35714285714285715,
5506
+ "mmlu_eval_accuracy_global_facts": 0.3,
5507
+ "mmlu_eval_accuracy_high_school_biology": 0.375,
5508
+ "mmlu_eval_accuracy_high_school_chemistry": 0.36363636363636365,
5509
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
5510
+ "mmlu_eval_accuracy_high_school_european_history": 0.3888888888888889,
5511
+ "mmlu_eval_accuracy_high_school_geography": 0.8181818181818182,
5512
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.5238095238095238,
5513
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.4418604651162791,
5514
+ "mmlu_eval_accuracy_high_school_mathematics": 0.2413793103448276,
5515
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.5384615384615384,
5516
+ "mmlu_eval_accuracy_high_school_physics": 0.23529411764705882,
5517
+ "mmlu_eval_accuracy_high_school_psychology": 0.8333333333333334,
5518
+ "mmlu_eval_accuracy_high_school_statistics": 0.4782608695652174,
5519
+ "mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364,
5520
+ "mmlu_eval_accuracy_high_school_world_history": 0.7307692307692307,
5521
+ "mmlu_eval_accuracy_human_aging": 0.5652173913043478,
5522
+ "mmlu_eval_accuracy_human_sexuality": 0.3333333333333333,
5523
+ "mmlu_eval_accuracy_international_law": 0.9230769230769231,
5524
+ "mmlu_eval_accuracy_jurisprudence": 0.45454545454545453,
5525
+ "mmlu_eval_accuracy_logical_fallacies": 0.6111111111111112,
5526
+ "mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
5527
+ "mmlu_eval_accuracy_management": 0.6363636363636364,
5528
+ "mmlu_eval_accuracy_marketing": 0.8,
5529
+ "mmlu_eval_accuracy_medical_genetics": 0.8181818181818182,
5530
+ "mmlu_eval_accuracy_miscellaneous": 0.6162790697674418,
5531
+ "mmlu_eval_accuracy_moral_disputes": 0.4473684210526316,
5532
+ "mmlu_eval_accuracy_moral_scenarios": 0.22,
5533
+ "mmlu_eval_accuracy_nutrition": 0.6666666666666666,
5534
+ "mmlu_eval_accuracy_philosophy": 0.5294117647058824,
5535
+ "mmlu_eval_accuracy_prehistory": 0.4857142857142857,
5536
+ "mmlu_eval_accuracy_professional_accounting": 0.22580645161290322,
5537
+ "mmlu_eval_accuracy_professional_law": 0.3,
5538
+ "mmlu_eval_accuracy_professional_medicine": 0.45161290322580644,
5539
+ "mmlu_eval_accuracy_professional_psychology": 0.43478260869565216,
5540
+ "mmlu_eval_accuracy_public_relations": 0.4166666666666667,
5541
+ "mmlu_eval_accuracy_security_studies": 0.4444444444444444,
5542
+ "mmlu_eval_accuracy_sociology": 0.6818181818181818,
5543
+ "mmlu_eval_accuracy_us_foreign_policy": 0.6363636363636364,
5544
+ "mmlu_eval_accuracy_virology": 0.4444444444444444,
5545
+ "mmlu_eval_accuracy_world_religions": 0.631578947368421,
5546
+ "mmlu_loss": 1.3609690375567727,
5547
+ "step": 5800
5548
+ },
5549
+ {
5550
+ "epoch": 1.47,
5551
+ "learning_rate": 0.0002,
5552
+ "loss": 0.6383,
5553
+ "step": 5810
5554
+ },
5555
+ {
5556
+ "epoch": 1.47,
5557
+ "learning_rate": 0.0002,
5558
+ "loss": 0.6575,
5559
+ "step": 5820
5560
+ },
5561
+ {
5562
+ "epoch": 1.47,
5563
+ "learning_rate": 0.0002,
5564
+ "loss": 0.5851,
5565
+ "step": 5830
5566
+ },
5567
+ {
5568
+ "epoch": 1.47,
5569
+ "learning_rate": 0.0002,
5570
+ "loss": 0.6267,
5571
+ "step": 5840
5572
+ },
5573
+ {
5574
+ "epoch": 1.48,
5575
+ "learning_rate": 0.0002,
5576
+ "loss": 0.6189,
5577
+ "step": 5850
5578
+ },
5579
+ {
5580
+ "epoch": 1.48,
5581
+ "learning_rate": 0.0002,
5582
+ "loss": 0.601,
5583
+ "step": 5860
5584
+ },
5585
+ {
5586
+ "epoch": 1.48,
5587
+ "learning_rate": 0.0002,
5588
+ "loss": 0.6597,
5589
+ "step": 5870
5590
+ },
5591
+ {
5592
+ "epoch": 1.48,
5593
+ "learning_rate": 0.0002,
5594
+ "loss": 0.5545,
5595
+ "step": 5880
5596
+ },
5597
+ {
5598
+ "epoch": 1.49,
5599
+ "learning_rate": 0.0002,
5600
+ "loss": 0.6664,
5601
+ "step": 5890
5602
+ },
5603
+ {
5604
+ "epoch": 1.49,
5605
+ "learning_rate": 0.0002,
5606
+ "loss": 0.6479,
5607
+ "step": 5900
5608
+ },
5609
+ {
5610
+ "epoch": 1.49,
5611
+ "learning_rate": 0.0002,
5612
+ "loss": 0.6259,
5613
+ "step": 5910
5614
+ },
5615
+ {
5616
+ "epoch": 1.49,
5617
+ "learning_rate": 0.0002,
5618
+ "loss": 0.5721,
5619
+ "step": 5920
5620
+ },
5621
+ {
5622
+ "epoch": 1.5,
5623
+ "learning_rate": 0.0002,
5624
+ "loss": 0.587,
5625
+ "step": 5930
5626
+ },
5627
+ {
5628
+ "epoch": 1.5,
5629
+ "learning_rate": 0.0002,
5630
+ "loss": 0.6236,
5631
+ "step": 5940
5632
+ },
5633
+ {
5634
+ "epoch": 1.5,
5635
+ "learning_rate": 0.0002,
5636
+ "loss": 0.6237,
5637
+ "step": 5950
5638
+ },
5639
+ {
5640
+ "epoch": 1.5,
5641
+ "learning_rate": 0.0002,
5642
+ "loss": 0.5352,
5643
+ "step": 5960
5644
+ },
5645
+ {
5646
+ "epoch": 1.51,
5647
+ "learning_rate": 0.0002,
5648
+ "loss": 0.5884,
5649
+ "step": 5970
5650
+ },
5651
+ {
5652
+ "epoch": 1.51,
5653
+ "learning_rate": 0.0002,
5654
+ "loss": 0.5936,
5655
+ "step": 5980
5656
+ },
5657
+ {
5658
+ "epoch": 1.51,
5659
+ "learning_rate": 0.0002,
5660
+ "loss": 0.613,
5661
+ "step": 5990
5662
+ },
5663
+ {
5664
+ "epoch": 1.51,
5665
+ "learning_rate": 0.0002,
5666
+ "loss": 0.6025,
5667
+ "step": 6000
5668
+ },
5669
+ {
5670
+ "epoch": 1.51,
5671
+ "eval_loss": 0.6665782928466797,
5672
+ "eval_runtime": 90.1302,
5673
+ "eval_samples_per_second": 11.095,
5674
+ "eval_steps_per_second": 5.548,
5675
+ "step": 6000
5676
+ },
5677
+ {
5678
+ "epoch": 1.51,
5679
+ "mmlu_eval_accuracy": 0.48103660388305747,
5680
+ "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
5681
+ "mmlu_eval_accuracy_anatomy": 0.6428571428571429,
5682
+ "mmlu_eval_accuracy_astronomy": 0.4375,
5683
+ "mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
5684
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5517241379310345,
5685
+ "mmlu_eval_accuracy_college_biology": 0.4375,
5686
+ "mmlu_eval_accuracy_college_chemistry": 0.25,
5687
+ "mmlu_eval_accuracy_college_computer_science": 0.36363636363636365,
5688
+ "mmlu_eval_accuracy_college_mathematics": 0.36363636363636365,
5689
+ "mmlu_eval_accuracy_college_medicine": 0.6818181818181818,
5690
+ "mmlu_eval_accuracy_college_physics": 0.2727272727272727,
5691
+ "mmlu_eval_accuracy_computer_security": 0.36363636363636365,
5692
+ "mmlu_eval_accuracy_conceptual_physics": 0.4230769230769231,
5693
+ "mmlu_eval_accuracy_econometrics": 0.3333333333333333,
5694
+ "mmlu_eval_accuracy_electrical_engineering": 0.3125,
5695
+ "mmlu_eval_accuracy_elementary_mathematics": 0.34146341463414637,
5696
+ "mmlu_eval_accuracy_formal_logic": 0.2857142857142857,
5697
+ "mmlu_eval_accuracy_global_facts": 0.3,
5698
+ "mmlu_eval_accuracy_high_school_biology": 0.4375,
5699
+ "mmlu_eval_accuracy_high_school_chemistry": 0.3181818181818182,
5700
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
5701
+ "mmlu_eval_accuracy_high_school_european_history": 0.3888888888888889,
5702
+ "mmlu_eval_accuracy_high_school_geography": 0.8181818181818182,
5703
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.5714285714285714,
5704
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.4418604651162791,
5705
+ "mmlu_eval_accuracy_high_school_mathematics": 0.2413793103448276,
5706
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.5769230769230769,
5707
+ "mmlu_eval_accuracy_high_school_physics": 0.23529411764705882,
5708
+ "mmlu_eval_accuracy_high_school_psychology": 0.8,
5709
+ "mmlu_eval_accuracy_high_school_statistics": 0.391304347826087,
5710
+ "mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364,
5711
+ "mmlu_eval_accuracy_high_school_world_history": 0.7692307692307693,
5712
+ "mmlu_eval_accuracy_human_aging": 0.5652173913043478,
5713
+ "mmlu_eval_accuracy_human_sexuality": 0.3333333333333333,
5714
+ "mmlu_eval_accuracy_international_law": 0.8461538461538461,
5715
+ "mmlu_eval_accuracy_jurisprudence": 0.45454545454545453,
5716
+ "mmlu_eval_accuracy_logical_fallacies": 0.6111111111111112,
5717
+ "mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
5718
+ "mmlu_eval_accuracy_management": 0.6363636363636364,
5719
+ "mmlu_eval_accuracy_marketing": 0.76,
5720
+ "mmlu_eval_accuracy_medical_genetics": 0.8181818181818182,
5721
+ "mmlu_eval_accuracy_miscellaneous": 0.5930232558139535,
5722
+ "mmlu_eval_accuracy_moral_disputes": 0.5,
5723
+ "mmlu_eval_accuracy_moral_scenarios": 0.22,
5724
+ "mmlu_eval_accuracy_nutrition": 0.7272727272727273,
5725
+ "mmlu_eval_accuracy_philosophy": 0.5294117647058824,
5726
+ "mmlu_eval_accuracy_prehistory": 0.45714285714285713,
5727
+ "mmlu_eval_accuracy_professional_accounting": 0.2903225806451613,
5728
+ "mmlu_eval_accuracy_professional_law": 0.3352941176470588,
5729
+ "mmlu_eval_accuracy_professional_medicine": 0.41935483870967744,
5730
+ "mmlu_eval_accuracy_professional_psychology": 0.42028985507246375,
5731
+ "mmlu_eval_accuracy_public_relations": 0.5,
5732
+ "mmlu_eval_accuracy_security_studies": 0.5555555555555556,
5733
+ "mmlu_eval_accuracy_sociology": 0.6818181818181818,
5734
+ "mmlu_eval_accuracy_us_foreign_policy": 0.6363636363636364,
5735
+ "mmlu_eval_accuracy_virology": 0.4444444444444444,
5736
+ "mmlu_eval_accuracy_world_religions": 0.631578947368421,
5737
+ "mmlu_loss": 1.198233921713057,
5738
+ "step": 6000
5739
+ },
5740
+ {
5741
+ "epoch": 1.52,
5742
+ "learning_rate": 0.0002,
5743
+ "loss": 0.6232,
5744
+ "step": 6010
5745
+ },
5746
+ {
5747
+ "epoch": 1.52,
5748
+ "learning_rate": 0.0002,
5749
+ "loss": 0.5916,
5750
+ "step": 6020
5751
+ },
5752
+ {
5753
+ "epoch": 1.52,
5754
+ "learning_rate": 0.0002,
5755
+ "loss": 0.6368,
5756
+ "step": 6030
5757
+ },
5758
+ {
5759
+ "epoch": 1.53,
5760
+ "learning_rate": 0.0002,
5761
+ "loss": 0.6426,
5762
+ "step": 6040
5763
+ },
5764
+ {
5765
+ "epoch": 1.53,
5766
+ "learning_rate": 0.0002,
5767
+ "loss": 0.5785,
5768
+ "step": 6050
5769
+ },
5770
+ {
5771
+ "epoch": 1.53,
5772
+ "learning_rate": 0.0002,
5773
+ "loss": 0.6331,
5774
+ "step": 6060
5775
+ },
5776
+ {
5777
+ "epoch": 1.53,
5778
+ "learning_rate": 0.0002,
5779
+ "loss": 0.5942,
5780
+ "step": 6070
5781
+ },
5782
+ {
5783
+ "epoch": 1.54,
5784
+ "learning_rate": 0.0002,
5785
+ "loss": 0.5549,
5786
+ "step": 6080
5787
+ },
5788
+ {
5789
+ "epoch": 1.54,
5790
+ "learning_rate": 0.0002,
5791
+ "loss": 0.6139,
5792
+ "step": 6090
5793
+ },
5794
+ {
5795
+ "epoch": 1.54,
5796
+ "learning_rate": 0.0002,
5797
+ "loss": 0.5967,
5798
+ "step": 6100
5799
+ },
5800
+ {
5801
+ "epoch": 1.54,
5802
+ "learning_rate": 0.0002,
5803
+ "loss": 0.6296,
5804
+ "step": 6110
5805
+ },
5806
+ {
5807
+ "epoch": 1.55,
5808
+ "learning_rate": 0.0002,
5809
+ "loss": 0.643,
5810
+ "step": 6120
5811
+ },
5812
+ {
5813
+ "epoch": 1.55,
5814
+ "learning_rate": 0.0002,
5815
+ "loss": 0.6347,
5816
+ "step": 6130
5817
+ },
5818
+ {
5819
+ "epoch": 1.55,
5820
+ "learning_rate": 0.0002,
5821
+ "loss": 0.5897,
5822
+ "step": 6140
5823
+ },
5824
+ {
5825
+ "epoch": 1.55,
5826
+ "learning_rate": 0.0002,
5827
+ "loss": 0.5889,
5828
+ "step": 6150
5829
+ },
5830
+ {
5831
+ "epoch": 1.56,
5832
+ "learning_rate": 0.0002,
5833
+ "loss": 0.6393,
5834
+ "step": 6160
5835
+ },
5836
+ {
5837
+ "epoch": 1.56,
5838
+ "learning_rate": 0.0002,
5839
+ "loss": 0.6255,
5840
+ "step": 6170
5841
+ },
5842
+ {
5843
+ "epoch": 1.56,
5844
+ "learning_rate": 0.0002,
5845
+ "loss": 0.621,
5846
+ "step": 6180
5847
+ },
5848
+ {
5849
+ "epoch": 1.56,
5850
+ "learning_rate": 0.0002,
5851
+ "loss": 0.636,
5852
+ "step": 6190
5853
+ },
5854
+ {
5855
+ "epoch": 1.57,
5856
+ "learning_rate": 0.0002,
5857
+ "loss": 0.607,
5858
+ "step": 6200
5859
+ },
5860
+ {
5861
+ "epoch": 1.57,
5862
+ "eval_loss": 0.6625620722770691,
5863
+ "eval_runtime": 90.2149,
5864
+ "eval_samples_per_second": 11.085,
5865
+ "eval_steps_per_second": 5.542,
5866
+ "step": 6200
5867
+ },
5868
+ {
5869
+ "epoch": 1.57,
5870
+ "mmlu_eval_accuracy": 0.4707159113919408,
5871
+ "mmlu_eval_accuracy_abstract_algebra": 0.36363636363636365,
5872
+ "mmlu_eval_accuracy_anatomy": 0.5,
5873
+ "mmlu_eval_accuracy_astronomy": 0.375,
5874
+ "mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
5875
+ "mmlu_eval_accuracy_clinical_knowledge": 0.4827586206896552,
5876
+ "mmlu_eval_accuracy_college_biology": 0.4375,
5877
+ "mmlu_eval_accuracy_college_chemistry": 0.375,
5878
+ "mmlu_eval_accuracy_college_computer_science": 0.36363636363636365,
5879
+ "mmlu_eval_accuracy_college_mathematics": 0.36363636363636365,
5880
+ "mmlu_eval_accuracy_college_medicine": 0.45454545454545453,
5881
+ "mmlu_eval_accuracy_college_physics": 0.36363636363636365,
5882
+ "mmlu_eval_accuracy_computer_security": 0.2727272727272727,
5883
+ "mmlu_eval_accuracy_conceptual_physics": 0.38461538461538464,
5884
+ "mmlu_eval_accuracy_econometrics": 0.25,
5885
+ "mmlu_eval_accuracy_electrical_engineering": 0.3125,
5886
+ "mmlu_eval_accuracy_elementary_mathematics": 0.36585365853658536,
5887
+ "mmlu_eval_accuracy_formal_logic": 0.2857142857142857,
5888
+ "mmlu_eval_accuracy_global_facts": 0.4,
5889
+ "mmlu_eval_accuracy_high_school_biology": 0.375,
5890
+ "mmlu_eval_accuracy_high_school_chemistry": 0.36363636363636365,
5891
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
5892
+ "mmlu_eval_accuracy_high_school_european_history": 0.3888888888888889,
5893
+ "mmlu_eval_accuracy_high_school_geography": 0.7727272727272727,
5894
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.5238095238095238,
5895
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.3953488372093023,
5896
+ "mmlu_eval_accuracy_high_school_mathematics": 0.20689655172413793,
5897
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.46153846153846156,
5898
+ "mmlu_eval_accuracy_high_school_physics": 0.23529411764705882,
5899
+ "mmlu_eval_accuracy_high_school_psychology": 0.75,
5900
+ "mmlu_eval_accuracy_high_school_statistics": 0.30434782608695654,
5901
+ "mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364,
5902
+ "mmlu_eval_accuracy_high_school_world_history": 0.7692307692307693,
5903
+ "mmlu_eval_accuracy_human_aging": 0.5652173913043478,
5904
+ "mmlu_eval_accuracy_human_sexuality": 0.3333333333333333,
5905
+ "mmlu_eval_accuracy_international_law": 0.9230769230769231,
5906
+ "mmlu_eval_accuracy_jurisprudence": 0.2727272727272727,
5907
+ "mmlu_eval_accuracy_logical_fallacies": 0.6666666666666666,
5908
+ "mmlu_eval_accuracy_machine_learning": 0.09090909090909091,
5909
+ "mmlu_eval_accuracy_management": 0.5454545454545454,
5910
+ "mmlu_eval_accuracy_marketing": 0.76,
5911
+ "mmlu_eval_accuracy_medical_genetics": 0.8181818181818182,
5912
+ "mmlu_eval_accuracy_miscellaneous": 0.6627906976744186,
5913
+ "mmlu_eval_accuracy_moral_disputes": 0.47368421052631576,
5914
+ "mmlu_eval_accuracy_moral_scenarios": 0.33,
5915
+ "mmlu_eval_accuracy_nutrition": 0.696969696969697,
5916
+ "mmlu_eval_accuracy_philosophy": 0.5882352941176471,
5917
+ "mmlu_eval_accuracy_prehistory": 0.42857142857142855,
5918
+ "mmlu_eval_accuracy_professional_accounting": 0.25806451612903225,
5919
+ "mmlu_eval_accuracy_professional_law": 0.34705882352941175,
5920
+ "mmlu_eval_accuracy_professional_medicine": 0.5161290322580645,
5921
+ "mmlu_eval_accuracy_professional_psychology": 0.4492753623188406,
5922
+ "mmlu_eval_accuracy_public_relations": 0.5,
5923
+ "mmlu_eval_accuracy_security_studies": 0.4074074074074074,
5924
+ "mmlu_eval_accuracy_sociology": 0.6363636363636364,
5925
+ "mmlu_eval_accuracy_us_foreign_policy": 0.6363636363636364,
5926
+ "mmlu_eval_accuracy_virology": 0.5,
5927
+ "mmlu_eval_accuracy_world_religions": 0.7894736842105263,
5928
+ "mmlu_loss": 1.3245997179892917,
5929
+ "step": 6200
5930
+ },
5931
+ {
5932
+ "epoch": 1.57,
5933
+ "learning_rate": 0.0002,
5934
+ "loss": 0.5666,
5935
+ "step": 6210
5936
+ },
5937
+ {
5938
+ "epoch": 1.57,
5939
+ "learning_rate": 0.0002,
5940
+ "loss": 0.59,
5941
+ "step": 6220
5942
+ },
5943
+ {
5944
+ "epoch": 1.57,
5945
+ "learning_rate": 0.0002,
5946
+ "loss": 0.5696,
5947
+ "step": 6230
5948
+ },
5949
+ {
5950
+ "epoch": 1.58,
5951
+ "learning_rate": 0.0002,
5952
+ "loss": 0.5514,
5953
+ "step": 6240
5954
+ },
5955
+ {
5956
+ "epoch": 1.58,
5957
+ "learning_rate": 0.0002,
5958
+ "loss": 0.6155,
5959
+ "step": 6250
5960
+ },
5961
+ {
5962
+ "epoch": 1.58,
5963
+ "learning_rate": 0.0002,
5964
+ "loss": 0.5959,
5965
+ "step": 6260
5966
+ },
5967
+ {
5968
+ "epoch": 1.58,
5969
+ "learning_rate": 0.0002,
5970
+ "loss": 0.6059,
5971
+ "step": 6270
5972
+ },
5973
+ {
5974
+ "epoch": 1.59,
5975
+ "learning_rate": 0.0002,
5976
+ "loss": 0.5903,
5977
+ "step": 6280
5978
+ },
5979
+ {
5980
+ "epoch": 1.59,
5981
+ "learning_rate": 0.0002,
5982
+ "loss": 0.5644,
5983
+ "step": 6290
5984
+ },
5985
+ {
5986
+ "epoch": 1.59,
5987
+ "learning_rate": 0.0002,
5988
+ "loss": 0.5893,
5989
+ "step": 6300
5990
+ },
5991
+ {
5992
+ "epoch": 1.59,
5993
+ "learning_rate": 0.0002,
5994
+ "loss": 0.5917,
5995
+ "step": 6310
5996
+ },
5997
+ {
5998
+ "epoch": 1.6,
5999
+ "learning_rate": 0.0002,
6000
+ "loss": 0.5714,
6001
+ "step": 6320
6002
+ },
6003
+ {
6004
+ "epoch": 1.6,
6005
+ "learning_rate": 0.0002,
6006
+ "loss": 0.609,
6007
+ "step": 6330
6008
+ },
6009
+ {
6010
+ "epoch": 1.6,
6011
+ "learning_rate": 0.0002,
6012
+ "loss": 0.5647,
6013
+ "step": 6340
6014
+ },
6015
+ {
6016
+ "epoch": 1.6,
6017
+ "learning_rate": 0.0002,
6018
+ "loss": 0.5692,
6019
+ "step": 6350
6020
+ },
6021
+ {
6022
+ "epoch": 1.61,
6023
+ "learning_rate": 0.0002,
6024
+ "loss": 0.5743,
6025
+ "step": 6360
6026
+ },
6027
+ {
6028
+ "epoch": 1.61,
6029
+ "learning_rate": 0.0002,
6030
+ "loss": 0.5906,
6031
+ "step": 6370
6032
+ },
6033
+ {
6034
+ "epoch": 1.61,
6035
+ "learning_rate": 0.0002,
6036
+ "loss": 0.6061,
6037
+ "step": 6380
6038
+ },
6039
+ {
6040
+ "epoch": 1.61,
6041
+ "learning_rate": 0.0002,
6042
+ "loss": 0.5892,
6043
+ "step": 6390
6044
+ },
6045
+ {
6046
+ "epoch": 1.62,
6047
+ "learning_rate": 0.0002,
6048
+ "loss": 0.5842,
6049
+ "step": 6400
6050
+ },
6051
+ {
6052
+ "epoch": 1.62,
6053
+ "eval_loss": 0.6594575047492981,
6054
+ "eval_runtime": 90.1103,
6055
+ "eval_samples_per_second": 11.098,
6056
+ "eval_steps_per_second": 5.549,
6057
+ "step": 6400
6058
+ },
6059
+ {
6060
+ "epoch": 1.62,
6061
+ "mmlu_eval_accuracy": 0.4775446061404259,
6062
+ "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
6063
+ "mmlu_eval_accuracy_anatomy": 0.5714285714285714,
6064
+ "mmlu_eval_accuracy_astronomy": 0.375,
6065
+ "mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
6066
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5517241379310345,
6067
+ "mmlu_eval_accuracy_college_biology": 0.375,
6068
+ "mmlu_eval_accuracy_college_chemistry": 0.25,
6069
+ "mmlu_eval_accuracy_college_computer_science": 0.36363636363636365,
6070
+ "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
6071
+ "mmlu_eval_accuracy_college_medicine": 0.5,
6072
+ "mmlu_eval_accuracy_college_physics": 0.36363636363636365,
6073
+ "mmlu_eval_accuracy_computer_security": 0.36363636363636365,
6074
+ "mmlu_eval_accuracy_conceptual_physics": 0.46153846153846156,
6075
+ "mmlu_eval_accuracy_econometrics": 0.3333333333333333,
6076
+ "mmlu_eval_accuracy_electrical_engineering": 0.3125,
6077
+ "mmlu_eval_accuracy_elementary_mathematics": 0.4146341463414634,
6078
+ "mmlu_eval_accuracy_formal_logic": 0.35714285714285715,
6079
+ "mmlu_eval_accuracy_global_facts": 0.3,
6080
+ "mmlu_eval_accuracy_high_school_biology": 0.375,
6081
+ "mmlu_eval_accuracy_high_school_chemistry": 0.3181818181818182,
6082
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
6083
+ "mmlu_eval_accuracy_high_school_european_history": 0.4444444444444444,
6084
+ "mmlu_eval_accuracy_high_school_geography": 0.7727272727272727,
6085
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.5714285714285714,
6086
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.4418604651162791,
6087
+ "mmlu_eval_accuracy_high_school_mathematics": 0.2413793103448276,
6088
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.6538461538461539,
6089
+ "mmlu_eval_accuracy_high_school_physics": 0.29411764705882354,
6090
+ "mmlu_eval_accuracy_high_school_psychology": 0.8,
6091
+ "mmlu_eval_accuracy_high_school_statistics": 0.391304347826087,
6092
+ "mmlu_eval_accuracy_high_school_us_history": 0.5909090909090909,
6093
+ "mmlu_eval_accuracy_high_school_world_history": 0.6923076923076923,
6094
+ "mmlu_eval_accuracy_human_aging": 0.5652173913043478,
6095
+ "mmlu_eval_accuracy_human_sexuality": 0.3333333333333333,
6096
+ "mmlu_eval_accuracy_international_law": 0.9230769230769231,
6097
+ "mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
6098
+ "mmlu_eval_accuracy_logical_fallacies": 0.6666666666666666,
6099
+ "mmlu_eval_accuracy_machine_learning": 0.09090909090909091,
6100
+ "mmlu_eval_accuracy_management": 0.6363636363636364,
6101
+ "mmlu_eval_accuracy_marketing": 0.68,
6102
+ "mmlu_eval_accuracy_medical_genetics": 0.8181818181818182,
6103
+ "mmlu_eval_accuracy_miscellaneous": 0.6395348837209303,
6104
+ "mmlu_eval_accuracy_moral_disputes": 0.5,
6105
+ "mmlu_eval_accuracy_moral_scenarios": 0.23,
6106
+ "mmlu_eval_accuracy_nutrition": 0.7575757575757576,
6107
+ "mmlu_eval_accuracy_philosophy": 0.5,
6108
+ "mmlu_eval_accuracy_prehistory": 0.4857142857142857,
6109
+ "mmlu_eval_accuracy_professional_accounting": 0.22580645161290322,
6110
+ "mmlu_eval_accuracy_professional_law": 0.3352941176470588,
6111
+ "mmlu_eval_accuracy_professional_medicine": 0.3870967741935484,
6112
+ "mmlu_eval_accuracy_professional_psychology": 0.43478260869565216,
6113
+ "mmlu_eval_accuracy_public_relations": 0.5,
6114
+ "mmlu_eval_accuracy_security_studies": 0.5555555555555556,
6115
+ "mmlu_eval_accuracy_sociology": 0.6818181818181818,
6116
+ "mmlu_eval_accuracy_us_foreign_policy": 0.6363636363636364,
6117
+ "mmlu_eval_accuracy_virology": 0.5,
6118
+ "mmlu_eval_accuracy_world_religions": 0.7368421052631579,
6119
+ "mmlu_loss": 1.528930509837427,
6120
+ "step": 6400
6121
+ },
6122
+ {
6123
+ "epoch": 1.62,
6124
+ "learning_rate": 0.0002,
6125
+ "loss": 0.6004,
6126
+ "step": 6410
6127
+ },
6128
+ {
6129
+ "epoch": 1.62,
6130
+ "learning_rate": 0.0002,
6131
+ "loss": 0.5904,
6132
+ "step": 6420
6133
+ },
6134
+ {
6135
+ "epoch": 1.62,
6136
+ "learning_rate": 0.0002,
6137
+ "loss": 0.5721,
6138
+ "step": 6430
6139
+ },
6140
+ {
6141
+ "epoch": 1.63,
6142
+ "learning_rate": 0.0002,
6143
+ "loss": 0.6393,
6144
+ "step": 6440
6145
+ },
6146
+ {
6147
+ "epoch": 1.63,
6148
+ "learning_rate": 0.0002,
6149
+ "loss": 0.6374,
6150
+ "step": 6450
6151
+ },
6152
+ {
6153
+ "epoch": 1.63,
6154
+ "learning_rate": 0.0002,
6155
+ "loss": 0.6234,
6156
+ "step": 6460
6157
+ },
6158
+ {
6159
+ "epoch": 1.63,
6160
+ "learning_rate": 0.0002,
6161
+ "loss": 0.5804,
6162
+ "step": 6470
6163
+ },
6164
+ {
6165
+ "epoch": 1.64,
6166
+ "learning_rate": 0.0002,
6167
+ "loss": 0.5908,
6168
+ "step": 6480
6169
+ },
6170
+ {
6171
+ "epoch": 1.64,
6172
+ "learning_rate": 0.0002,
6173
+ "loss": 0.584,
6174
+ "step": 6490
6175
+ },
6176
+ {
6177
+ "epoch": 1.64,
6178
+ "learning_rate": 0.0002,
6179
+ "loss": 0.5936,
6180
+ "step": 6500
6181
+ },
6182
+ {
6183
+ "epoch": 1.64,
6184
+ "learning_rate": 0.0002,
6185
+ "loss": 0.6205,
6186
+ "step": 6510
6187
+ },
6188
+ {
6189
+ "epoch": 1.65,
6190
+ "learning_rate": 0.0002,
6191
+ "loss": 0.6582,
6192
+ "step": 6520
6193
+ },
6194
+ {
6195
+ "epoch": 1.65,
6196
+ "learning_rate": 0.0002,
6197
+ "loss": 0.5781,
6198
+ "step": 6530
6199
+ },
6200
+ {
6201
+ "epoch": 1.65,
6202
+ "learning_rate": 0.0002,
6203
+ "loss": 0.5593,
6204
+ "step": 6540
6205
+ },
6206
+ {
6207
+ "epoch": 1.65,
6208
+ "learning_rate": 0.0002,
6209
+ "loss": 0.613,
6210
+ "step": 6550
6211
+ },
6212
+ {
6213
+ "epoch": 1.66,
6214
+ "learning_rate": 0.0002,
6215
+ "loss": 0.6927,
6216
+ "step": 6560
6217
+ },
6218
+ {
6219
+ "epoch": 1.66,
6220
+ "learning_rate": 0.0002,
6221
+ "loss": 0.6175,
6222
+ "step": 6570
6223
+ },
6224
+ {
6225
+ "epoch": 1.66,
6226
+ "learning_rate": 0.0002,
6227
+ "loss": 0.561,
6228
+ "step": 6580
6229
+ },
6230
+ {
6231
+ "epoch": 1.66,
6232
+ "learning_rate": 0.0002,
6233
+ "loss": 0.6447,
6234
+ "step": 6590
6235
+ },
6236
+ {
6237
+ "epoch": 1.67,
6238
+ "learning_rate": 0.0002,
6239
+ "loss": 0.5607,
6240
+ "step": 6600
6241
+ },
6242
+ {
6243
+ "epoch": 1.67,
6244
+ "eval_loss": 0.6628819704055786,
6245
+ "eval_runtime": 90.1695,
6246
+ "eval_samples_per_second": 11.09,
6247
+ "eval_steps_per_second": 5.545,
6248
+ "step": 6600
6249
+ },
6250
+ {
6251
+ "epoch": 1.67,
6252
+ "mmlu_eval_accuracy": 0.47400923350924634,
6253
+ "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
6254
+ "mmlu_eval_accuracy_anatomy": 0.5714285714285714,
6255
+ "mmlu_eval_accuracy_astronomy": 0.375,
6256
+ "mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
6257
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5862068965517241,
6258
+ "mmlu_eval_accuracy_college_biology": 0.4375,
6259
+ "mmlu_eval_accuracy_college_chemistry": 0.25,
6260
+ "mmlu_eval_accuracy_college_computer_science": 0.2727272727272727,
6261
+ "mmlu_eval_accuracy_college_mathematics": 0.36363636363636365,
6262
+ "mmlu_eval_accuracy_college_medicine": 0.5,
6263
+ "mmlu_eval_accuracy_college_physics": 0.36363636363636365,
6264
+ "mmlu_eval_accuracy_computer_security": 0.36363636363636365,
6265
+ "mmlu_eval_accuracy_conceptual_physics": 0.38461538461538464,
6266
+ "mmlu_eval_accuracy_econometrics": 0.3333333333333333,
6267
+ "mmlu_eval_accuracy_electrical_engineering": 0.3125,
6268
+ "mmlu_eval_accuracy_elementary_mathematics": 0.36585365853658536,
6269
+ "mmlu_eval_accuracy_formal_logic": 0.2857142857142857,
6270
+ "mmlu_eval_accuracy_global_facts": 0.3,
6271
+ "mmlu_eval_accuracy_high_school_biology": 0.40625,
6272
+ "mmlu_eval_accuracy_high_school_chemistry": 0.36363636363636365,
6273
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
6274
+ "mmlu_eval_accuracy_high_school_european_history": 0.5,
6275
+ "mmlu_eval_accuracy_high_school_geography": 0.8181818181818182,
6276
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.47619047619047616,
6277
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.32558139534883723,
6278
+ "mmlu_eval_accuracy_high_school_mathematics": 0.2413793103448276,
6279
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.6923076923076923,
6280
+ "mmlu_eval_accuracy_high_school_physics": 0.23529411764705882,
6281
+ "mmlu_eval_accuracy_high_school_psychology": 0.7833333333333333,
6282
+ "mmlu_eval_accuracy_high_school_statistics": 0.391304347826087,
6283
+ "mmlu_eval_accuracy_high_school_us_history": 0.5909090909090909,
6284
+ "mmlu_eval_accuracy_high_school_world_history": 0.7307692307692307,
6285
+ "mmlu_eval_accuracy_human_aging": 0.5652173913043478,
6286
+ "mmlu_eval_accuracy_human_sexuality": 0.3333333333333333,
6287
+ "mmlu_eval_accuracy_international_law": 0.9230769230769231,
6288
+ "mmlu_eval_accuracy_jurisprudence": 0.45454545454545453,
6289
+ "mmlu_eval_accuracy_logical_fallacies": 0.6111111111111112,
6290
+ "mmlu_eval_accuracy_machine_learning": 0.09090909090909091,
6291
+ "mmlu_eval_accuracy_management": 0.6363636363636364,
6292
+ "mmlu_eval_accuracy_marketing": 0.68,
6293
+ "mmlu_eval_accuracy_medical_genetics": 0.8181818181818182,
6294
+ "mmlu_eval_accuracy_miscellaneous": 0.627906976744186,
6295
+ "mmlu_eval_accuracy_moral_disputes": 0.5,
6296
+ "mmlu_eval_accuracy_moral_scenarios": 0.23,
6297
+ "mmlu_eval_accuracy_nutrition": 0.7272727272727273,
6298
+ "mmlu_eval_accuracy_philosophy": 0.5294117647058824,
6299
+ "mmlu_eval_accuracy_prehistory": 0.45714285714285713,
6300
+ "mmlu_eval_accuracy_professional_accounting": 0.2903225806451613,
6301
+ "mmlu_eval_accuracy_professional_law": 0.32941176470588235,
6302
+ "mmlu_eval_accuracy_professional_medicine": 0.3548387096774194,
6303
+ "mmlu_eval_accuracy_professional_psychology": 0.4057971014492754,
6304
+ "mmlu_eval_accuracy_public_relations": 0.5833333333333334,
6305
+ "mmlu_eval_accuracy_security_studies": 0.48148148148148145,
6306
+ "mmlu_eval_accuracy_sociology": 0.6818181818181818,
6307
+ "mmlu_eval_accuracy_us_foreign_policy": 0.6363636363636364,
6308
+ "mmlu_eval_accuracy_virology": 0.4444444444444444,
6309
+ "mmlu_eval_accuracy_world_religions": 0.631578947368421,
6310
+ "mmlu_loss": 1.2749472340622396,
6311
+ "step": 6600
6312
+ },
6313
+ {
6314
+ "epoch": 1.67,
6315
+ "learning_rate": 0.0002,
6316
+ "loss": 0.5903,
6317
+ "step": 6610
6318
+ },
6319
+ {
6320
+ "epoch": 1.67,
6321
+ "learning_rate": 0.0002,
6322
+ "loss": 0.6233,
6323
+ "step": 6620
6324
+ },
6325
+ {
6326
+ "epoch": 1.67,
6327
+ "learning_rate": 0.0002,
6328
+ "loss": 0.5499,
6329
+ "step": 6630
6330
+ },
6331
+ {
6332
+ "epoch": 1.68,
6333
+ "learning_rate": 0.0002,
6334
+ "loss": 0.5773,
6335
+ "step": 6640
6336
+ },
6337
+ {
6338
+ "epoch": 1.68,
6339
+ "learning_rate": 0.0002,
6340
+ "loss": 0.5682,
6341
+ "step": 6650
6342
+ },
6343
+ {
6344
+ "epoch": 1.68,
6345
+ "learning_rate": 0.0002,
6346
+ "loss": 0.6576,
6347
+ "step": 6660
6348
+ },
6349
+ {
6350
+ "epoch": 1.68,
6351
+ "learning_rate": 0.0002,
6352
+ "loss": 0.6291,
6353
+ "step": 6670
6354
+ },
6355
+ {
6356
+ "epoch": 1.69,
6357
+ "learning_rate": 0.0002,
6358
+ "loss": 0.5888,
6359
+ "step": 6680
6360
+ },
6361
+ {
6362
+ "epoch": 1.69,
6363
+ "learning_rate": 0.0002,
6364
+ "loss": 0.6009,
6365
+ "step": 6690
6366
+ },
6367
+ {
6368
+ "epoch": 1.69,
6369
+ "learning_rate": 0.0002,
6370
+ "loss": 0.5833,
6371
+ "step": 6700
6372
+ },
6373
+ {
6374
+ "epoch": 1.69,
6375
+ "learning_rate": 0.0002,
6376
+ "loss": 0.6066,
6377
+ "step": 6710
6378
+ },
6379
+ {
6380
+ "epoch": 1.7,
6381
+ "learning_rate": 0.0002,
6382
+ "loss": 0.6287,
6383
+ "step": 6720
6384
+ },
6385
+ {
6386
+ "epoch": 1.7,
6387
+ "learning_rate": 0.0002,
6388
+ "loss": 0.6478,
6389
+ "step": 6730
6390
+ },
6391
+ {
6392
+ "epoch": 1.7,
6393
+ "learning_rate": 0.0002,
6394
+ "loss": 0.6049,
6395
+ "step": 6740
6396
+ },
6397
+ {
6398
+ "epoch": 1.7,
6399
+ "learning_rate": 0.0002,
6400
+ "loss": 0.6321,
6401
+ "step": 6750
6402
+ },
6403
+ {
6404
+ "epoch": 1.71,
6405
+ "learning_rate": 0.0002,
6406
+ "loss": 0.5809,
6407
+ "step": 6760
6408
+ },
6409
+ {
6410
+ "epoch": 1.71,
6411
+ "learning_rate": 0.0002,
6412
+ "loss": 0.612,
6413
+ "step": 6770
6414
+ },
6415
+ {
6416
+ "epoch": 1.71,
6417
+ "learning_rate": 0.0002,
6418
+ "loss": 0.6505,
6419
+ "step": 6780
6420
+ },
6421
+ {
6422
+ "epoch": 1.71,
6423
+ "learning_rate": 0.0002,
6424
+ "loss": 0.573,
6425
+ "step": 6790
6426
+ },
6427
+ {
6428
+ "epoch": 1.72,
6429
+ "learning_rate": 0.0002,
6430
+ "loss": 0.5864,
6431
+ "step": 6800
6432
+ },
6433
+ {
6434
+ "epoch": 1.72,
6435
+ "eval_loss": 0.6619049906730652,
6436
+ "eval_runtime": 90.3264,
6437
+ "eval_samples_per_second": 11.071,
6438
+ "eval_steps_per_second": 5.535,
6439
+ "step": 6800
6440
+ },
6441
+ {
6442
+ "epoch": 1.72,
6443
+ "mmlu_eval_accuracy": 0.4746064288496086,
6444
+ "mmlu_eval_accuracy_abstract_algebra": 0.36363636363636365,
6445
+ "mmlu_eval_accuracy_anatomy": 0.5714285714285714,
6446
+ "mmlu_eval_accuracy_astronomy": 0.3125,
6447
+ "mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
6448
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5862068965517241,
6449
+ "mmlu_eval_accuracy_college_biology": 0.5625,
6450
+ "mmlu_eval_accuracy_college_chemistry": 0.125,
6451
+ "mmlu_eval_accuracy_college_computer_science": 0.36363636363636365,
6452
+ "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
6453
+ "mmlu_eval_accuracy_college_medicine": 0.5,
6454
+ "mmlu_eval_accuracy_college_physics": 0.45454545454545453,
6455
+ "mmlu_eval_accuracy_computer_security": 0.36363636363636365,
6456
+ "mmlu_eval_accuracy_conceptual_physics": 0.34615384615384615,
6457
+ "mmlu_eval_accuracy_econometrics": 0.3333333333333333,
6458
+ "mmlu_eval_accuracy_electrical_engineering": 0.3125,
6459
+ "mmlu_eval_accuracy_elementary_mathematics": 0.34146341463414637,
6460
+ "mmlu_eval_accuracy_formal_logic": 0.2857142857142857,
6461
+ "mmlu_eval_accuracy_global_facts": 0.4,
6462
+ "mmlu_eval_accuracy_high_school_biology": 0.46875,
6463
+ "mmlu_eval_accuracy_high_school_chemistry": 0.3181818181818182,
6464
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
6465
+ "mmlu_eval_accuracy_high_school_european_history": 0.5555555555555556,
6466
+ "mmlu_eval_accuracy_high_school_geography": 0.8636363636363636,
6467
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.5714285714285714,
6468
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.37209302325581395,
6469
+ "mmlu_eval_accuracy_high_school_mathematics": 0.20689655172413793,
6470
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.5384615384615384,
6471
+ "mmlu_eval_accuracy_high_school_physics": 0.23529411764705882,
6472
+ "mmlu_eval_accuracy_high_school_psychology": 0.7666666666666667,
6473
+ "mmlu_eval_accuracy_high_school_statistics": 0.2608695652173913,
6474
+ "mmlu_eval_accuracy_high_school_us_history": 0.5909090909090909,
6475
+ "mmlu_eval_accuracy_high_school_world_history": 0.7307692307692307,
6476
+ "mmlu_eval_accuracy_human_aging": 0.6086956521739131,
6477
+ "mmlu_eval_accuracy_human_sexuality": 0.3333333333333333,
6478
+ "mmlu_eval_accuracy_international_law": 0.9230769230769231,
6479
+ "mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
6480
+ "mmlu_eval_accuracy_logical_fallacies": 0.6666666666666666,
6481
+ "mmlu_eval_accuracy_machine_learning": 0.09090909090909091,
6482
+ "mmlu_eval_accuracy_management": 0.5454545454545454,
6483
+ "mmlu_eval_accuracy_marketing": 0.72,
6484
+ "mmlu_eval_accuracy_medical_genetics": 0.9090909090909091,
6485
+ "mmlu_eval_accuracy_miscellaneous": 0.6162790697674418,
6486
+ "mmlu_eval_accuracy_moral_disputes": 0.47368421052631576,
6487
+ "mmlu_eval_accuracy_moral_scenarios": 0.22,
6488
+ "mmlu_eval_accuracy_nutrition": 0.696969696969697,
6489
+ "mmlu_eval_accuracy_philosophy": 0.5294117647058824,
6490
+ "mmlu_eval_accuracy_prehistory": 0.45714285714285713,
6491
+ "mmlu_eval_accuracy_professional_accounting": 0.22580645161290322,
6492
+ "mmlu_eval_accuracy_professional_law": 0.32941176470588235,
6493
+ "mmlu_eval_accuracy_professional_medicine": 0.5161290322580645,
6494
+ "mmlu_eval_accuracy_professional_psychology": 0.42028985507246375,
6495
+ "mmlu_eval_accuracy_public_relations": 0.5833333333333334,
6496
+ "mmlu_eval_accuracy_security_studies": 0.4444444444444444,
6497
+ "mmlu_eval_accuracy_sociology": 0.5909090909090909,
6498
+ "mmlu_eval_accuracy_us_foreign_policy": 0.6363636363636364,
6499
+ "mmlu_eval_accuracy_virology": 0.4444444444444444,
6500
+ "mmlu_eval_accuracy_world_religions": 0.631578947368421,
6501
+ "mmlu_loss": 1.3764885561273241,
6502
+ "step": 6800
6503
+ },
6504
+ {
6505
+ "epoch": 1.72,
6506
+ "learning_rate": 0.0002,
6507
+ "loss": 0.6156,
6508
+ "step": 6810
6509
+ },
6510
+ {
6511
+ "epoch": 1.72,
6512
+ "learning_rate": 0.0002,
6513
+ "loss": 0.6501,
6514
+ "step": 6820
6515
+ },
6516
+ {
6517
+ "epoch": 1.72,
6518
+ "learning_rate": 0.0002,
6519
+ "loss": 0.6569,
6520
+ "step": 6830
6521
+ },
6522
+ {
6523
+ "epoch": 1.73,
6524
+ "learning_rate": 0.0002,
6525
+ "loss": 0.5909,
6526
+ "step": 6840
6527
+ },
6528
+ {
6529
+ "epoch": 1.73,
6530
+ "learning_rate": 0.0002,
6531
+ "loss": 0.6419,
6532
+ "step": 6850
6533
+ },
6534
+ {
6535
+ "epoch": 1.73,
6536
+ "learning_rate": 0.0002,
6537
+ "loss": 0.6209,
6538
+ "step": 6860
6539
+ },
6540
+ {
6541
+ "epoch": 1.73,
6542
+ "learning_rate": 0.0002,
6543
+ "loss": 0.6302,
6544
+ "step": 6870
6545
+ },
6546
+ {
6547
+ "epoch": 1.74,
6548
+ "learning_rate": 0.0002,
6549
+ "loss": 0.5826,
6550
+ "step": 6880
6551
+ },
6552
+ {
6553
+ "epoch": 1.74,
6554
+ "learning_rate": 0.0002,
6555
+ "loss": 0.5915,
6556
+ "step": 6890
6557
+ },
6558
+ {
6559
+ "epoch": 1.74,
6560
+ "learning_rate": 0.0002,
6561
+ "loss": 0.6164,
6562
+ "step": 6900
6563
+ },
6564
+ {
6565
+ "epoch": 1.74,
6566
+ "learning_rate": 0.0002,
6567
+ "loss": 0.6244,
6568
+ "step": 6910
6569
+ },
6570
+ {
6571
+ "epoch": 1.75,
6572
+ "learning_rate": 0.0002,
6573
+ "loss": 0.5823,
6574
+ "step": 6920
6575
+ },
6576
+ {
6577
+ "epoch": 1.75,
6578
+ "learning_rate": 0.0002,
6579
+ "loss": 0.6334,
6580
+ "step": 6930
6581
+ },
6582
+ {
6583
+ "epoch": 1.75,
6584
+ "learning_rate": 0.0002,
6585
+ "loss": 0.5943,
6586
+ "step": 6940
6587
+ },
6588
+ {
6589
+ "epoch": 1.75,
6590
+ "learning_rate": 0.0002,
6591
+ "loss": 0.5736,
6592
+ "step": 6950
6593
+ },
6594
+ {
6595
+ "epoch": 1.76,
6596
+ "learning_rate": 0.0002,
6597
+ "loss": 0.6621,
6598
+ "step": 6960
6599
+ },
6600
+ {
6601
+ "epoch": 1.76,
6602
+ "learning_rate": 0.0002,
6603
+ "loss": 0.6195,
6604
+ "step": 6970
6605
+ },
6606
+ {
6607
+ "epoch": 1.76,
6608
+ "learning_rate": 0.0002,
6609
+ "loss": 0.6461,
6610
+ "step": 6980
6611
+ },
6612
+ {
6613
+ "epoch": 1.76,
6614
+ "learning_rate": 0.0002,
6615
+ "loss": 0.6268,
6616
+ "step": 6990
6617
+ },
6618
+ {
6619
+ "epoch": 1.77,
6620
+ "learning_rate": 0.0002,
6621
+ "loss": 0.6197,
6622
+ "step": 7000
6623
+ },
6624
+ {
6625
+ "epoch": 1.77,
6626
+ "eval_loss": 0.6594330072402954,
6627
+ "eval_runtime": 90.3142,
6628
+ "eval_samples_per_second": 11.072,
6629
+ "eval_steps_per_second": 5.536,
6630
+ "step": 7000
6631
+ },
6632
+ {
6633
+ "epoch": 1.77,
6634
+ "mmlu_eval_accuracy": 0.49011680387550416,
6635
+ "mmlu_eval_accuracy_abstract_algebra": 0.36363636363636365,
6636
+ "mmlu_eval_accuracy_anatomy": 0.5714285714285714,
6637
+ "mmlu_eval_accuracy_astronomy": 0.4375,
6638
+ "mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
6639
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5862068965517241,
6640
+ "mmlu_eval_accuracy_college_biology": 0.5,
6641
+ "mmlu_eval_accuracy_college_chemistry": 0.25,
6642
+ "mmlu_eval_accuracy_college_computer_science": 0.2727272727272727,
6643
+ "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
6644
+ "mmlu_eval_accuracy_college_medicine": 0.45454545454545453,
6645
+ "mmlu_eval_accuracy_college_physics": 0.45454545454545453,
6646
+ "mmlu_eval_accuracy_computer_security": 0.36363636363636365,
6647
+ "mmlu_eval_accuracy_conceptual_physics": 0.38461538461538464,
6648
+ "mmlu_eval_accuracy_econometrics": 0.3333333333333333,
6649
+ "mmlu_eval_accuracy_electrical_engineering": 0.3125,
6650
+ "mmlu_eval_accuracy_elementary_mathematics": 0.34146341463414637,
6651
+ "mmlu_eval_accuracy_formal_logic": 0.2857142857142857,
6652
+ "mmlu_eval_accuracy_global_facts": 0.4,
6653
+ "mmlu_eval_accuracy_high_school_biology": 0.40625,
6654
+ "mmlu_eval_accuracy_high_school_chemistry": 0.36363636363636365,
6655
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
6656
+ "mmlu_eval_accuracy_high_school_european_history": 0.5555555555555556,
6657
+ "mmlu_eval_accuracy_high_school_geography": 0.8636363636363636,
6658
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.6190476190476191,
6659
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.4186046511627907,
6660
+ "mmlu_eval_accuracy_high_school_mathematics": 0.20689655172413793,
6661
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.5384615384615384,
6662
+ "mmlu_eval_accuracy_high_school_physics": 0.23529411764705882,
6663
+ "mmlu_eval_accuracy_high_school_psychology": 0.8166666666666667,
6664
+ "mmlu_eval_accuracy_high_school_statistics": 0.391304347826087,
6665
+ "mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364,
6666
+ "mmlu_eval_accuracy_high_school_world_history": 0.8076923076923077,
6667
+ "mmlu_eval_accuracy_human_aging": 0.6086956521739131,
6668
+ "mmlu_eval_accuracy_human_sexuality": 0.3333333333333333,
6669
+ "mmlu_eval_accuracy_international_law": 0.9230769230769231,
6670
+ "mmlu_eval_accuracy_jurisprudence": 0.45454545454545453,
6671
+ "mmlu_eval_accuracy_logical_fallacies": 0.6666666666666666,
6672
+ "mmlu_eval_accuracy_machine_learning": 0.09090909090909091,
6673
+ "mmlu_eval_accuracy_management": 0.5454545454545454,
6674
+ "mmlu_eval_accuracy_marketing": 0.72,
6675
+ "mmlu_eval_accuracy_medical_genetics": 0.8181818181818182,
6676
+ "mmlu_eval_accuracy_miscellaneous": 0.6511627906976745,
6677
+ "mmlu_eval_accuracy_moral_disputes": 0.5,
6678
+ "mmlu_eval_accuracy_moral_scenarios": 0.25,
6679
+ "mmlu_eval_accuracy_nutrition": 0.7575757575757576,
6680
+ "mmlu_eval_accuracy_philosophy": 0.5588235294117647,
6681
+ "mmlu_eval_accuracy_prehistory": 0.4857142857142857,
6682
+ "mmlu_eval_accuracy_professional_accounting": 0.2903225806451613,
6683
+ "mmlu_eval_accuracy_professional_law": 0.3352941176470588,
6684
+ "mmlu_eval_accuracy_professional_medicine": 0.4838709677419355,
6685
+ "mmlu_eval_accuracy_professional_psychology": 0.42028985507246375,
6686
+ "mmlu_eval_accuracy_public_relations": 0.5833333333333334,
6687
+ "mmlu_eval_accuracy_security_studies": 0.5555555555555556,
6688
+ "mmlu_eval_accuracy_sociology": 0.5909090909090909,
6689
+ "mmlu_eval_accuracy_us_foreign_policy": 0.6363636363636364,
6690
+ "mmlu_eval_accuracy_virology": 0.5,
6691
+ "mmlu_eval_accuracy_world_religions": 0.631578947368421,
6692
+ "mmlu_loss": 1.4939264588972296,
6693
+ "step": 7000
6694
+ },
6695
+ {
6696
+ "epoch": 1.77,
6697
+ "learning_rate": 0.0002,
6698
+ "loss": 0.5944,
6699
+ "step": 7010
6700
+ },
6701
+ {
6702
+ "epoch": 1.77,
6703
+ "learning_rate": 0.0002,
6704
+ "loss": 0.6036,
6705
+ "step": 7020
6706
+ },
6707
+ {
6708
+ "epoch": 1.78,
6709
+ "learning_rate": 0.0002,
6710
+ "loss": 0.5791,
6711
+ "step": 7030
6712
+ },
6713
+ {
6714
+ "epoch": 1.78,
6715
+ "learning_rate": 0.0002,
6716
+ "loss": 0.6439,
6717
+ "step": 7040
6718
+ },
6719
+ {
6720
+ "epoch": 1.78,
6721
+ "learning_rate": 0.0002,
6722
+ "loss": 0.6184,
6723
+ "step": 7050
6724
+ },
6725
+ {
6726
+ "epoch": 1.78,
6727
+ "learning_rate": 0.0002,
6728
+ "loss": 0.5771,
6729
+ "step": 7060
6730
+ },
6731
+ {
6732
+ "epoch": 1.79,
6733
+ "learning_rate": 0.0002,
6734
+ "loss": 0.5936,
6735
+ "step": 7070
6736
+ },
6737
+ {
6738
+ "epoch": 1.79,
6739
+ "learning_rate": 0.0002,
6740
+ "loss": 0.6187,
6741
+ "step": 7080
6742
+ },
6743
+ {
6744
+ "epoch": 1.79,
6745
+ "learning_rate": 0.0002,
6746
+ "loss": 0.5953,
6747
+ "step": 7090
6748
+ },
6749
+ {
6750
+ "epoch": 1.79,
6751
+ "learning_rate": 0.0002,
6752
+ "loss": 0.6141,
6753
+ "step": 7100
6754
+ },
6755
+ {
6756
+ "epoch": 1.8,
6757
+ "learning_rate": 0.0002,
6758
+ "loss": 0.6058,
6759
+ "step": 7110
6760
+ },
6761
+ {
6762
+ "epoch": 1.8,
6763
+ "learning_rate": 0.0002,
6764
+ "loss": 0.585,
6765
+ "step": 7120
6766
+ },
6767
+ {
6768
+ "epoch": 1.8,
6769
+ "learning_rate": 0.0002,
6770
+ "loss": 0.6093,
6771
+ "step": 7130
6772
+ },
6773
+ {
6774
+ "epoch": 1.8,
6775
+ "learning_rate": 0.0002,
6776
+ "loss": 0.6084,
6777
+ "step": 7140
6778
+ },
6779
+ {
6780
+ "epoch": 1.81,
6781
+ "learning_rate": 0.0002,
6782
+ "loss": 0.6429,
6783
+ "step": 7150
6784
+ },
6785
+ {
6786
+ "epoch": 1.81,
6787
+ "learning_rate": 0.0002,
6788
+ "loss": 0.6485,
6789
+ "step": 7160
6790
+ },
6791
+ {
6792
+ "epoch": 1.81,
6793
+ "learning_rate": 0.0002,
6794
+ "loss": 0.5481,
6795
+ "step": 7170
6796
+ },
6797
+ {
6798
+ "epoch": 1.81,
6799
+ "learning_rate": 0.0002,
6800
+ "loss": 0.5975,
6801
+ "step": 7180
6802
+ },
6803
+ {
6804
+ "epoch": 1.82,
6805
+ "learning_rate": 0.0002,
6806
+ "loss": 0.6025,
6807
+ "step": 7190
6808
+ },
6809
+ {
6810
+ "epoch": 1.82,
6811
+ "learning_rate": 0.0002,
6812
+ "loss": 0.6041,
6813
+ "step": 7200
6814
+ },
6815
+ {
6816
+ "epoch": 1.82,
6817
+ "eval_loss": 0.6614479422569275,
6818
+ "eval_runtime": 90.115,
6819
+ "eval_samples_per_second": 11.097,
6820
+ "eval_steps_per_second": 5.548,
6821
+ "step": 7200
6822
+ },
6823
+ {
6824
+ "epoch": 1.82,
6825
+ "mmlu_eval_accuracy": 0.4455606639158589,
6826
+ "mmlu_eval_accuracy_abstract_algebra": 0.36363636363636365,
6827
+ "mmlu_eval_accuracy_anatomy": 0.5714285714285714,
6828
+ "mmlu_eval_accuracy_astronomy": 0.3125,
6829
+ "mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
6830
+ "mmlu_eval_accuracy_clinical_knowledge": 0.4827586206896552,
6831
+ "mmlu_eval_accuracy_college_biology": 0.3125,
6832
+ "mmlu_eval_accuracy_college_chemistry": 0.125,
6833
+ "mmlu_eval_accuracy_college_computer_science": 0.2727272727272727,
6834
+ "mmlu_eval_accuracy_college_mathematics": 0.36363636363636365,
6835
+ "mmlu_eval_accuracy_college_medicine": 0.45454545454545453,
6836
+ "mmlu_eval_accuracy_college_physics": 0.36363636363636365,
6837
+ "mmlu_eval_accuracy_computer_security": 0.2727272727272727,
6838
+ "mmlu_eval_accuracy_conceptual_physics": 0.38461538461538464,
6839
+ "mmlu_eval_accuracy_econometrics": 0.25,
6840
+ "mmlu_eval_accuracy_electrical_engineering": 0.25,
6841
+ "mmlu_eval_accuracy_elementary_mathematics": 0.2926829268292683,
6842
+ "mmlu_eval_accuracy_formal_logic": 0.14285714285714285,
6843
+ "mmlu_eval_accuracy_global_facts": 0.4,
6844
+ "mmlu_eval_accuracy_high_school_biology": 0.375,
6845
+ "mmlu_eval_accuracy_high_school_chemistry": 0.18181818181818182,
6846
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
6847
+ "mmlu_eval_accuracy_high_school_european_history": 0.5555555555555556,
6848
+ "mmlu_eval_accuracy_high_school_geography": 0.8636363636363636,
6849
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.42857142857142855,
6850
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.37209302325581395,
6851
+ "mmlu_eval_accuracy_high_school_mathematics": 0.27586206896551724,
6852
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.38461538461538464,
6853
+ "mmlu_eval_accuracy_high_school_physics": 0.11764705882352941,
6854
+ "mmlu_eval_accuracy_high_school_psychology": 0.7833333333333333,
6855
+ "mmlu_eval_accuracy_high_school_statistics": 0.21739130434782608,
6856
+ "mmlu_eval_accuracy_high_school_us_history": 0.6818181818181818,
6857
+ "mmlu_eval_accuracy_high_school_world_history": 0.6923076923076923,
6858
+ "mmlu_eval_accuracy_human_aging": 0.6086956521739131,
6859
+ "mmlu_eval_accuracy_human_sexuality": 0.3333333333333333,
6860
+ "mmlu_eval_accuracy_international_law": 0.9230769230769231,
6861
+ "mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
6862
+ "mmlu_eval_accuracy_logical_fallacies": 0.6111111111111112,
6863
+ "mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
6864
+ "mmlu_eval_accuracy_management": 0.45454545454545453,
6865
+ "mmlu_eval_accuracy_marketing": 0.72,
6866
+ "mmlu_eval_accuracy_medical_genetics": 0.9090909090909091,
6867
+ "mmlu_eval_accuracy_miscellaneous": 0.627906976744186,
6868
+ "mmlu_eval_accuracy_moral_disputes": 0.47368421052631576,
6869
+ "mmlu_eval_accuracy_moral_scenarios": 0.31,
6870
+ "mmlu_eval_accuracy_nutrition": 0.6363636363636364,
6871
+ "mmlu_eval_accuracy_philosophy": 0.5588235294117647,
6872
+ "mmlu_eval_accuracy_prehistory": 0.4,
6873
+ "mmlu_eval_accuracy_professional_accounting": 0.3225806451612903,
6874
+ "mmlu_eval_accuracy_professional_law": 0.3,
6875
+ "mmlu_eval_accuracy_professional_medicine": 0.4838709677419355,
6876
+ "mmlu_eval_accuracy_professional_psychology": 0.42028985507246375,
6877
+ "mmlu_eval_accuracy_public_relations": 0.5833333333333334,
6878
+ "mmlu_eval_accuracy_security_studies": 0.4074074074074074,
6879
+ "mmlu_eval_accuracy_sociology": 0.5909090909090909,
6880
+ "mmlu_eval_accuracy_us_foreign_policy": 0.5454545454545454,
6881
+ "mmlu_eval_accuracy_virology": 0.4444444444444444,
6882
+ "mmlu_eval_accuracy_world_religions": 0.631578947368421,
6883
+ "mmlu_loss": 1.5667742720316347,
6884
+ "step": 7200
6885
+ },
6886
+ {
6887
+ "epoch": 1.82,
6888
+ "learning_rate": 0.0002,
6889
+ "loss": 0.6105,
6890
+ "step": 7210
6891
+ },
6892
+ {
6893
+ "epoch": 1.82,
6894
+ "learning_rate": 0.0002,
6895
+ "loss": 0.6258,
6896
+ "step": 7220
6897
+ },
6898
+ {
6899
+ "epoch": 1.83,
6900
+ "learning_rate": 0.0002,
6901
+ "loss": 0.6131,
6902
+ "step": 7230
6903
+ },
6904
+ {
6905
+ "epoch": 1.83,
6906
+ "learning_rate": 0.0002,
6907
+ "loss": 0.6326,
6908
+ "step": 7240
6909
+ },
6910
+ {
6911
+ "epoch": 1.83,
6912
+ "learning_rate": 0.0002,
6913
+ "loss": 0.6787,
6914
+ "step": 7250
6915
+ },
6916
+ {
6917
+ "epoch": 1.83,
6918
+ "learning_rate": 0.0002,
6919
+ "loss": 0.6273,
6920
+ "step": 7260
6921
+ },
6922
+ {
6923
+ "epoch": 1.84,
6924
+ "learning_rate": 0.0002,
6925
+ "loss": 0.5891,
6926
+ "step": 7270
6927
+ },
6928
+ {
6929
+ "epoch": 1.84,
6930
+ "learning_rate": 0.0002,
6931
+ "loss": 0.6091,
6932
+ "step": 7280
6933
+ },
6934
+ {
6935
+ "epoch": 1.84,
6936
+ "learning_rate": 0.0002,
6937
+ "loss": 0.5896,
6938
+ "step": 7290
6939
+ },
6940
+ {
6941
+ "epoch": 1.84,
6942
+ "learning_rate": 0.0002,
6943
+ "loss": 0.5806,
6944
+ "step": 7300
6945
+ },
6946
+ {
6947
+ "epoch": 1.85,
6948
+ "learning_rate": 0.0002,
6949
+ "loss": 0.5901,
6950
+ "step": 7310
6951
+ },
6952
+ {
6953
+ "epoch": 1.85,
6954
+ "learning_rate": 0.0002,
6955
+ "loss": 0.565,
6956
+ "step": 7320
6957
+ },
6958
+ {
6959
+ "epoch": 1.85,
6960
+ "learning_rate": 0.0002,
6961
+ "loss": 0.6361,
6962
+ "step": 7330
6963
+ },
6964
+ {
6965
+ "epoch": 1.85,
6966
+ "learning_rate": 0.0002,
6967
+ "loss": 0.6096,
6968
+ "step": 7340
6969
+ },
6970
+ {
6971
+ "epoch": 1.86,
6972
+ "learning_rate": 0.0002,
6973
+ "loss": 0.6298,
6974
+ "step": 7350
6975
+ },
6976
+ {
6977
+ "epoch": 1.86,
6978
+ "learning_rate": 0.0002,
6979
+ "loss": 0.623,
6980
+ "step": 7360
6981
+ },
6982
+ {
6983
+ "epoch": 1.86,
6984
+ "learning_rate": 0.0002,
6985
+ "loss": 0.5954,
6986
+ "step": 7370
6987
+ },
6988
+ {
6989
+ "epoch": 1.86,
6990
+ "learning_rate": 0.0002,
6991
+ "loss": 0.5609,
6992
+ "step": 7380
6993
+ },
6994
+ {
6995
+ "epoch": 1.87,
6996
+ "learning_rate": 0.0002,
6997
+ "loss": 0.6413,
6998
+ "step": 7390
6999
+ },
7000
+ {
7001
+ "epoch": 1.87,
7002
+ "learning_rate": 0.0002,
7003
+ "loss": 0.6359,
7004
+ "step": 7400
7005
+ },
7006
+ {
7007
+ "epoch": 1.87,
7008
+ "eval_loss": 0.661052942276001,
7009
+ "eval_runtime": 90.1541,
7010
+ "eval_samples_per_second": 11.092,
7011
+ "eval_steps_per_second": 5.546,
7012
+ "step": 7400
7013
+ },
7014
+ {
7015
+ "epoch": 1.87,
7016
+ "mmlu_eval_accuracy": 0.4529178211073842,
7017
+ "mmlu_eval_accuracy_abstract_algebra": 0.36363636363636365,
7018
+ "mmlu_eval_accuracy_anatomy": 0.5714285714285714,
7019
+ "mmlu_eval_accuracy_astronomy": 0.375,
7020
+ "mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
7021
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5172413793103449,
7022
+ "mmlu_eval_accuracy_college_biology": 0.3125,
7023
+ "mmlu_eval_accuracy_college_chemistry": 0.125,
7024
+ "mmlu_eval_accuracy_college_computer_science": 0.18181818181818182,
7025
+ "mmlu_eval_accuracy_college_mathematics": 0.36363636363636365,
7026
+ "mmlu_eval_accuracy_college_medicine": 0.36363636363636365,
7027
+ "mmlu_eval_accuracy_college_physics": 0.36363636363636365,
7028
+ "mmlu_eval_accuracy_computer_security": 0.2727272727272727,
7029
+ "mmlu_eval_accuracy_conceptual_physics": 0.38461538461538464,
7030
+ "mmlu_eval_accuracy_econometrics": 0.25,
7031
+ "mmlu_eval_accuracy_electrical_engineering": 0.3125,
7032
+ "mmlu_eval_accuracy_elementary_mathematics": 0.3170731707317073,
7033
+ "mmlu_eval_accuracy_formal_logic": 0.14285714285714285,
7034
+ "mmlu_eval_accuracy_global_facts": 0.3,
7035
+ "mmlu_eval_accuracy_high_school_biology": 0.40625,
7036
+ "mmlu_eval_accuracy_high_school_chemistry": 0.18181818181818182,
7037
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
7038
+ "mmlu_eval_accuracy_high_school_european_history": 0.5555555555555556,
7039
+ "mmlu_eval_accuracy_high_school_geography": 0.8636363636363636,
7040
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.42857142857142855,
7041
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.37209302325581395,
7042
+ "mmlu_eval_accuracy_high_school_mathematics": 0.2413793103448276,
7043
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.3076923076923077,
7044
+ "mmlu_eval_accuracy_high_school_physics": 0.17647058823529413,
7045
+ "mmlu_eval_accuracy_high_school_psychology": 0.8,
7046
+ "mmlu_eval_accuracy_high_school_statistics": 0.2608695652173913,
7047
+ "mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364,
7048
+ "mmlu_eval_accuracy_high_school_world_history": 0.7307692307692307,
7049
+ "mmlu_eval_accuracy_human_aging": 0.5652173913043478,
7050
+ "mmlu_eval_accuracy_human_sexuality": 0.3333333333333333,
7051
+ "mmlu_eval_accuracy_international_law": 0.8461538461538461,
7052
+ "mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
7053
+ "mmlu_eval_accuracy_logical_fallacies": 0.6111111111111112,
7054
+ "mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
7055
+ "mmlu_eval_accuracy_management": 0.5454545454545454,
7056
+ "mmlu_eval_accuracy_marketing": 0.76,
7057
+ "mmlu_eval_accuracy_medical_genetics": 0.9090909090909091,
7058
+ "mmlu_eval_accuracy_miscellaneous": 0.6511627906976745,
7059
+ "mmlu_eval_accuracy_moral_disputes": 0.5,
7060
+ "mmlu_eval_accuracy_moral_scenarios": 0.36,
7061
+ "mmlu_eval_accuracy_nutrition": 0.6060606060606061,
7062
+ "mmlu_eval_accuracy_philosophy": 0.5882352941176471,
7063
+ "mmlu_eval_accuracy_prehistory": 0.4,
7064
+ "mmlu_eval_accuracy_professional_accounting": 0.3225806451612903,
7065
+ "mmlu_eval_accuracy_professional_law": 0.3,
7066
+ "mmlu_eval_accuracy_professional_medicine": 0.45161290322580644,
7067
+ "mmlu_eval_accuracy_professional_psychology": 0.4057971014492754,
7068
+ "mmlu_eval_accuracy_public_relations": 0.6666666666666666,
7069
+ "mmlu_eval_accuracy_security_studies": 0.4074074074074074,
7070
+ "mmlu_eval_accuracy_sociology": 0.5909090909090909,
7071
+ "mmlu_eval_accuracy_us_foreign_policy": 0.6363636363636364,
7072
+ "mmlu_eval_accuracy_virology": 0.4444444444444444,
7073
+ "mmlu_eval_accuracy_world_religions": 0.7894736842105263,
7074
+ "mmlu_loss": 1.2937584632993056,
7075
+ "step": 7400
7076
+ },
7077
+ {
7078
+ "epoch": 1.87,
7079
+ "learning_rate": 0.0002,
7080
+ "loss": 0.6037,
7081
+ "step": 7410
7082
+ },
7083
+ {
7084
+ "epoch": 1.87,
7085
+ "learning_rate": 0.0002,
7086
+ "loss": 0.6327,
7087
+ "step": 7420
7088
+ },
7089
+ {
7090
+ "epoch": 1.88,
7091
+ "learning_rate": 0.0002,
7092
+ "loss": 0.5989,
7093
+ "step": 7430
7094
+ },
7095
+ {
7096
+ "epoch": 1.88,
7097
+ "learning_rate": 0.0002,
7098
+ "loss": 0.5877,
7099
+ "step": 7440
7100
+ },
7101
+ {
7102
+ "epoch": 1.88,
7103
+ "learning_rate": 0.0002,
7104
+ "loss": 0.6165,
7105
+ "step": 7450
7106
+ },
7107
+ {
7108
+ "epoch": 1.88,
7109
+ "learning_rate": 0.0002,
7110
+ "loss": 0.587,
7111
+ "step": 7460
7112
+ },
7113
+ {
7114
+ "epoch": 1.89,
7115
+ "learning_rate": 0.0002,
7116
+ "loss": 0.6302,
7117
+ "step": 7470
7118
+ },
7119
+ {
7120
+ "epoch": 1.89,
7121
+ "learning_rate": 0.0002,
7122
+ "loss": 0.6358,
7123
+ "step": 7480
7124
+ },
7125
+ {
7126
+ "epoch": 1.89,
7127
+ "learning_rate": 0.0002,
7128
+ "loss": 0.6242,
7129
+ "step": 7490
7130
+ },
7131
+ {
7132
+ "epoch": 1.89,
7133
+ "learning_rate": 0.0002,
7134
+ "loss": 0.6924,
7135
+ "step": 7500
7136
+ },
7137
+ {
7138
+ "epoch": 1.9,
7139
+ "learning_rate": 0.0002,
7140
+ "loss": 0.5764,
7141
+ "step": 7510
7142
+ },
7143
+ {
7144
+ "epoch": 1.9,
7145
+ "learning_rate": 0.0002,
7146
+ "loss": 0.6344,
7147
+ "step": 7520
7148
+ },
7149
+ {
7150
+ "epoch": 1.9,
7151
+ "learning_rate": 0.0002,
7152
+ "loss": 0.6287,
7153
+ "step": 7530
7154
+ },
7155
+ {
7156
+ "epoch": 1.9,
7157
+ "learning_rate": 0.0002,
7158
+ "loss": 0.6249,
7159
+ "step": 7540
7160
+ },
7161
+ {
7162
+ "epoch": 1.91,
7163
+ "learning_rate": 0.0002,
7164
+ "loss": 0.6064,
7165
+ "step": 7550
7166
+ },
7167
+ {
7168
+ "epoch": 1.91,
7169
+ "learning_rate": 0.0002,
7170
+ "loss": 0.651,
7171
+ "step": 7560
7172
+ },
7173
+ {
7174
+ "epoch": 1.91,
7175
+ "learning_rate": 0.0002,
7176
+ "loss": 0.5961,
7177
+ "step": 7570
7178
+ },
7179
+ {
7180
+ "epoch": 1.91,
7181
+ "learning_rate": 0.0002,
7182
+ "loss": 0.5942,
7183
+ "step": 7580
7184
+ },
7185
+ {
7186
+ "epoch": 1.92,
7187
+ "learning_rate": 0.0002,
7188
+ "loss": 0.5791,
7189
+ "step": 7590
7190
+ },
7191
+ {
7192
+ "epoch": 1.92,
7193
+ "learning_rate": 0.0002,
7194
+ "loss": 0.5959,
7195
+ "step": 7600
7196
+ },
7197
+ {
7198
+ "epoch": 1.92,
7199
+ "eval_loss": 0.6617178320884705,
7200
+ "eval_runtime": 90.1895,
7201
+ "eval_samples_per_second": 11.088,
7202
+ "eval_steps_per_second": 5.544,
7203
+ "step": 7600
7204
+ },
7205
+ {
7206
+ "epoch": 1.92,
7207
+ "mmlu_eval_accuracy": 0.47253648996773845,
7208
+ "mmlu_eval_accuracy_abstract_algebra": 0.36363636363636365,
7209
+ "mmlu_eval_accuracy_anatomy": 0.5714285714285714,
7210
+ "mmlu_eval_accuracy_astronomy": 0.4375,
7211
+ "mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
7212
+ "mmlu_eval_accuracy_clinical_knowledge": 0.4482758620689655,
7213
+ "mmlu_eval_accuracy_college_biology": 0.375,
7214
+ "mmlu_eval_accuracy_college_chemistry": 0.0,
7215
+ "mmlu_eval_accuracy_college_computer_science": 0.36363636363636365,
7216
+ "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
7217
+ "mmlu_eval_accuracy_college_medicine": 0.36363636363636365,
7218
+ "mmlu_eval_accuracy_college_physics": 0.36363636363636365,
7219
+ "mmlu_eval_accuracy_computer_security": 0.36363636363636365,
7220
+ "mmlu_eval_accuracy_conceptual_physics": 0.46153846153846156,
7221
+ "mmlu_eval_accuracy_econometrics": 0.16666666666666666,
7222
+ "mmlu_eval_accuracy_electrical_engineering": 0.3125,
7223
+ "mmlu_eval_accuracy_elementary_mathematics": 0.34146341463414637,
7224
+ "mmlu_eval_accuracy_formal_logic": 0.21428571428571427,
7225
+ "mmlu_eval_accuracy_global_facts": 0.4,
7226
+ "mmlu_eval_accuracy_high_school_biology": 0.40625,
7227
+ "mmlu_eval_accuracy_high_school_chemistry": 0.3181818181818182,
7228
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
7229
+ "mmlu_eval_accuracy_high_school_european_history": 0.6666666666666666,
7230
+ "mmlu_eval_accuracy_high_school_geography": 0.9090909090909091,
7231
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.5714285714285714,
7232
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.3953488372093023,
7233
+ "mmlu_eval_accuracy_high_school_mathematics": 0.20689655172413793,
7234
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.38461538461538464,
7235
+ "mmlu_eval_accuracy_high_school_physics": 0.11764705882352941,
7236
+ "mmlu_eval_accuracy_high_school_psychology": 0.7666666666666667,
7237
+ "mmlu_eval_accuracy_high_school_statistics": 0.34782608695652173,
7238
+ "mmlu_eval_accuracy_high_school_us_history": 0.6818181818181818,
7239
+ "mmlu_eval_accuracy_high_school_world_history": 0.6923076923076923,
7240
+ "mmlu_eval_accuracy_human_aging": 0.6956521739130435,
7241
+ "mmlu_eval_accuracy_human_sexuality": 0.3333333333333333,
7242
+ "mmlu_eval_accuracy_international_law": 0.8461538461538461,
7243
+ "mmlu_eval_accuracy_jurisprudence": 0.2727272727272727,
7244
+ "mmlu_eval_accuracy_logical_fallacies": 0.6111111111111112,
7245
+ "mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
7246
+ "mmlu_eval_accuracy_management": 0.5454545454545454,
7247
+ "mmlu_eval_accuracy_marketing": 0.84,
7248
+ "mmlu_eval_accuracy_medical_genetics": 0.9090909090909091,
7249
+ "mmlu_eval_accuracy_miscellaneous": 0.6627906976744186,
7250
+ "mmlu_eval_accuracy_moral_disputes": 0.5263157894736842,
7251
+ "mmlu_eval_accuracy_moral_scenarios": 0.26,
7252
+ "mmlu_eval_accuracy_nutrition": 0.6363636363636364,
7253
+ "mmlu_eval_accuracy_philosophy": 0.5294117647058824,
7254
+ "mmlu_eval_accuracy_prehistory": 0.42857142857142855,
7255
+ "mmlu_eval_accuracy_professional_accounting": 0.3548387096774194,
7256
+ "mmlu_eval_accuracy_professional_law": 0.3588235294117647,
7257
+ "mmlu_eval_accuracy_professional_medicine": 0.5806451612903226,
7258
+ "mmlu_eval_accuracy_professional_psychology": 0.42028985507246375,
7259
+ "mmlu_eval_accuracy_public_relations": 0.5833333333333334,
7260
+ "mmlu_eval_accuracy_security_studies": 0.4074074074074074,
7261
+ "mmlu_eval_accuracy_sociology": 0.6363636363636364,
7262
+ "mmlu_eval_accuracy_us_foreign_policy": 0.6363636363636364,
7263
+ "mmlu_eval_accuracy_virology": 0.5555555555555556,
7264
+ "mmlu_eval_accuracy_world_religions": 0.7368421052631579,
7265
+ "mmlu_loss": 1.3078787350934729,
7266
+ "step": 7600
7267
+ },
7268
+ {
7269
+ "epoch": 1.92,
7270
+ "learning_rate": 0.0002,
7271
+ "loss": 0.6239,
7272
+ "step": 7610
7273
+ },
7274
+ {
7275
+ "epoch": 1.92,
7276
+ "learning_rate": 0.0002,
7277
+ "loss": 0.5632,
7278
+ "step": 7620
7279
+ },
7280
+ {
7281
+ "epoch": 1.93,
7282
+ "learning_rate": 0.0002,
7283
+ "loss": 0.603,
7284
+ "step": 7630
7285
+ },
7286
+ {
7287
+ "epoch": 1.93,
7288
+ "learning_rate": 0.0002,
7289
+ "loss": 0.6124,
7290
+ "step": 7640
7291
+ },
7292
+ {
7293
+ "epoch": 1.93,
7294
+ "learning_rate": 0.0002,
7295
+ "loss": 0.6273,
7296
+ "step": 7650
7297
+ },
7298
+ {
7299
+ "epoch": 1.93,
7300
+ "learning_rate": 0.0002,
7301
+ "loss": 0.5902,
7302
+ "step": 7660
7303
+ },
7304
+ {
7305
+ "epoch": 1.94,
7306
+ "learning_rate": 0.0002,
7307
+ "loss": 0.6705,
7308
+ "step": 7670
7309
+ },
7310
+ {
7311
+ "epoch": 1.94,
7312
+ "learning_rate": 0.0002,
7313
+ "loss": 0.6246,
7314
+ "step": 7680
7315
+ },
7316
+ {
7317
+ "epoch": 1.94,
7318
+ "learning_rate": 0.0002,
7319
+ "loss": 0.6702,
7320
+ "step": 7690
7321
+ },
7322
+ {
7323
+ "epoch": 1.94,
7324
+ "learning_rate": 0.0002,
7325
+ "loss": 0.5483,
7326
+ "step": 7700
7327
+ },
7328
+ {
7329
+ "epoch": 1.95,
7330
+ "learning_rate": 0.0002,
7331
+ "loss": 0.6525,
7332
+ "step": 7710
7333
+ },
7334
+ {
7335
+ "epoch": 1.95,
7336
+ "learning_rate": 0.0002,
7337
+ "loss": 0.6,
7338
+ "step": 7720
7339
+ },
7340
+ {
7341
+ "epoch": 1.95,
7342
+ "learning_rate": 0.0002,
7343
+ "loss": 0.639,
7344
+ "step": 7730
7345
+ },
7346
+ {
7347
+ "epoch": 1.95,
7348
+ "learning_rate": 0.0002,
7349
+ "loss": 0.5842,
7350
+ "step": 7740
7351
+ },
7352
+ {
7353
+ "epoch": 1.96,
7354
+ "learning_rate": 0.0002,
7355
+ "loss": 0.6308,
7356
+ "step": 7750
7357
+ },
7358
+ {
7359
+ "epoch": 1.96,
7360
+ "learning_rate": 0.0002,
7361
+ "loss": 0.5541,
7362
+ "step": 7760
7363
+ },
7364
+ {
7365
+ "epoch": 1.96,
7366
+ "learning_rate": 0.0002,
7367
+ "loss": 0.6203,
7368
+ "step": 7770
7369
+ },
7370
+ {
7371
+ "epoch": 1.96,
7372
+ "learning_rate": 0.0002,
7373
+ "loss": 0.6364,
7374
+ "step": 7780
7375
+ },
7376
+ {
7377
+ "epoch": 1.97,
7378
+ "learning_rate": 0.0002,
7379
+ "loss": 0.6032,
7380
+ "step": 7790
7381
+ },
7382
+ {
7383
+ "epoch": 1.97,
7384
+ "learning_rate": 0.0002,
7385
+ "loss": 0.6613,
7386
+ "step": 7800
7387
+ },
7388
+ {
7389
+ "epoch": 1.97,
7390
+ "eval_loss": 0.654138445854187,
7391
+ "eval_runtime": 90.1806,
7392
+ "eval_samples_per_second": 11.089,
7393
+ "eval_steps_per_second": 5.544,
7394
+ "step": 7800
7395
+ },
7396
+ {
7397
+ "epoch": 1.97,
7398
+ "mmlu_eval_accuracy": 0.4630593326728225,
7399
+ "mmlu_eval_accuracy_abstract_algebra": 0.36363636363636365,
7400
+ "mmlu_eval_accuracy_anatomy": 0.5714285714285714,
7401
+ "mmlu_eval_accuracy_astronomy": 0.375,
7402
+ "mmlu_eval_accuracy_business_ethics": 0.5454545454545454,
7403
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5172413793103449,
7404
+ "mmlu_eval_accuracy_college_biology": 0.5,
7405
+ "mmlu_eval_accuracy_college_chemistry": 0.0,
7406
+ "mmlu_eval_accuracy_college_computer_science": 0.2727272727272727,
7407
+ "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
7408
+ "mmlu_eval_accuracy_college_medicine": 0.36363636363636365,
7409
+ "mmlu_eval_accuracy_college_physics": 0.36363636363636365,
7410
+ "mmlu_eval_accuracy_computer_security": 0.2727272727272727,
7411
+ "mmlu_eval_accuracy_conceptual_physics": 0.4230769230769231,
7412
+ "mmlu_eval_accuracy_econometrics": 0.25,
7413
+ "mmlu_eval_accuracy_electrical_engineering": 0.3125,
7414
+ "mmlu_eval_accuracy_elementary_mathematics": 0.3170731707317073,
7415
+ "mmlu_eval_accuracy_formal_logic": 0.14285714285714285,
7416
+ "mmlu_eval_accuracy_global_facts": 0.3,
7417
+ "mmlu_eval_accuracy_high_school_biology": 0.4375,
7418
+ "mmlu_eval_accuracy_high_school_chemistry": 0.22727272727272727,
7419
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
7420
+ "mmlu_eval_accuracy_high_school_european_history": 0.5555555555555556,
7421
+ "mmlu_eval_accuracy_high_school_geography": 0.8636363636363636,
7422
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.47619047619047616,
7423
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.3953488372093023,
7424
+ "mmlu_eval_accuracy_high_school_mathematics": 0.20689655172413793,
7425
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.4230769230769231,
7426
+ "mmlu_eval_accuracy_high_school_physics": 0.17647058823529413,
7427
+ "mmlu_eval_accuracy_high_school_psychology": 0.7833333333333333,
7428
+ "mmlu_eval_accuracy_high_school_statistics": 0.2608695652173913,
7429
+ "mmlu_eval_accuracy_high_school_us_history": 0.5909090909090909,
7430
+ "mmlu_eval_accuracy_high_school_world_history": 0.7692307692307693,
7431
+ "mmlu_eval_accuracy_human_aging": 0.6086956521739131,
7432
+ "mmlu_eval_accuracy_human_sexuality": 0.3333333333333333,
7433
+ "mmlu_eval_accuracy_international_law": 0.8461538461538461,
7434
+ "mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
7435
+ "mmlu_eval_accuracy_logical_fallacies": 0.6666666666666666,
7436
+ "mmlu_eval_accuracy_machine_learning": 0.09090909090909091,
7437
+ "mmlu_eval_accuracy_management": 0.5454545454545454,
7438
+ "mmlu_eval_accuracy_marketing": 0.76,
7439
+ "mmlu_eval_accuracy_medical_genetics": 0.9090909090909091,
7440
+ "mmlu_eval_accuracy_miscellaneous": 0.627906976744186,
7441
+ "mmlu_eval_accuracy_moral_disputes": 0.5,
7442
+ "mmlu_eval_accuracy_moral_scenarios": 0.23,
7443
+ "mmlu_eval_accuracy_nutrition": 0.7272727272727273,
7444
+ "mmlu_eval_accuracy_philosophy": 0.5588235294117647,
7445
+ "mmlu_eval_accuracy_prehistory": 0.4,
7446
+ "mmlu_eval_accuracy_professional_accounting": 0.3225806451612903,
7447
+ "mmlu_eval_accuracy_professional_law": 0.3235294117647059,
7448
+ "mmlu_eval_accuracy_professional_medicine": 0.5483870967741935,
7449
+ "mmlu_eval_accuracy_professional_psychology": 0.43478260869565216,
7450
+ "mmlu_eval_accuracy_public_relations": 0.6666666666666666,
7451
+ "mmlu_eval_accuracy_security_studies": 0.4444444444444444,
7452
+ "mmlu_eval_accuracy_sociology": 0.6363636363636364,
7453
+ "mmlu_eval_accuracy_us_foreign_policy": 0.7272727272727273,
7454
+ "mmlu_eval_accuracy_virology": 0.5,
7455
+ "mmlu_eval_accuracy_world_religions": 0.7368421052631579,
7456
+ "mmlu_loss": 1.3784169822775665,
7457
+ "step": 7800
7458
  }
7459
  ],
7460
  "max_steps": 10000,
7461
  "num_train_epochs": 3,
7462
+ "total_flos": 4.6261150789922e+17,
7463
  "trial_name": null,
7464
  "trial_params": null
7465
  }
{checkpoint-5600 → checkpoint-7800}/training_args.bin RENAMED
File without changes